Blaed

joined 2 years ago
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3
submitted 2 years ago by Blaed to c/llm
 

Click Here to be Taken to the Megathread!

from [email protected]

Vicuna v1.5 Has Been Released!

Shoutout to [email protected] for catching this in an earlier post.

Given Vicuna was a widely appreciated member of the original Llama series, it'll be exciting to see this model evolve and adapt with fresh datasets and new training and fine-tuning approaches.

Feel free using this megathread to chat about Vicuna and any of your experiences with Vicuna v1.5!

Starting off with Vicuna v1.5

TheBloke is already sharing models!

Vicuna v1.5 GPTQ

7B

13B


Vicuna Model Card

Model Details

Vicuna is a chat assistant fine-tuned from Llama 2 on user-shared conversations collected from ShareGPT.

Developed by: LMSYS

  • Model type: An auto-regressive language model based on the transformer architecture
  • License: Llama 2 Community License Agreement
  • Finetuned from model: Llama 2

Model Sources

Uses

The primary use of Vicuna is for research on large language models and chatbots. The target userbase includes researchers and hobbyists interested in natural language processing, machine learning, and artificial intelligence.

How to Get Started with the Model

Training Details

Vicuna v1.5 is fine-tuned from Llama 2 using supervised instruction. The model was trained on approximately 125K conversations from ShareGPT.com.

For additional details, please refer to the "Training Details of Vicuna Models" section in the appendix of the linked paper.

Evaluation Results

Vicuna Evaluation Results

Vicuna is evaluated using standard benchmarks, human preferences, and LLM-as-a-judge. For more detailed results, please refer to the paper and leaderboard.

 

Click Here to be Taken to the Megathread!

from [email protected]

Vicuna v1.5 Has Been Released!

Shoutout to [email protected] for catching this in an earlier post.

Given Vicuna was a widely appreciated member of the original Llama series, it'll be exciting to see this model evolve and adapt with fresh datasets and new training and fine-tuning approaches.

Feel free using this megathread to chat about Vicuna and any of your experiences with Vicuna v1.5!

Starting off with Vicuna v1.5

TheBloke is already sharing models!

Vicuna v1.5 GPTQ

7B

13B


Vicuna Model Card

Model Details

Vicuna is a chat assistant fine-tuned from Llama 2 on user-shared conversations collected from ShareGPT.

Developed by: LMSYS

  • Model type: An auto-regressive language model based on the transformer architecture
  • License: Llama 2 Community License Agreement
  • Finetuned from model: Llama 2

Model Sources

Uses

The primary use of Vicuna is for research on large language models and chatbots. The target userbase includes researchers and hobbyists interested in natural language processing, machine learning, and artificial intelligence.

How to Get Started with the Model

Training Details

Vicuna v1.5 is fine-tuned from Llama 2 using supervised instruction. The model was trained on approximately 125K conversations from ShareGPT.com.

For additional details, please refer to the "Training Details of Vicuna Models" section in the appendix of the linked paper.

Evaluation Results

Vicuna Evaluation Results

Vicuna is evaluated using standard benchmarks, human preferences, and LLM-as-a-judge. For more detailed results, please refer to the paper and leaderboard.

 

Click Here to be Taken to the Megathread!

from [email protected]

Vicuna v1.5 Has Been Released!

Shoutout to [email protected] for catching this in an earlier post.

Given Vicuna was a widely appreciated member of the original Llama series, it'll be exciting to see this model evolve and adapt with fresh datasets and new training and fine-tuning approaches.

Feel free using this megathread to chat about Vicuna and any of your experiences with Vicuna v1.5!

Starting off with Vicuna v1.5

TheBloke is already sharing models!

Vicuna v1.5 GPTQ

7B

13B


Vicuna Model Card

Model Details

Vicuna is a chat assistant fine-tuned from Llama 2 on user-shared conversations collected from ShareGPT.

Developed by: LMSYS

  • Model type: An auto-regressive language model based on the transformer architecture
  • License: Llama 2 Community License Agreement
  • Finetuned from model: Llama 2

Model Sources

Uses

The primary use of Vicuna is for research on large language models and chatbots. The target userbase includes researchers and hobbyists interested in natural language processing, machine learning, and artificial intelligence.

How to Get Started with the Model

Training Details

Vicuna v1.5 is fine-tuned from Llama 2 using supervised instruction. The model was trained on approximately 125K conversations from ShareGPT.com.

For additional details, please refer to the "Training Details of Vicuna Models" section in the appendix of the linked paper.

Evaluation Results

Vicuna Evaluation Results

Vicuna is evaluated using standard benchmarks, human preferences, and LLM-as-a-judge. For more detailed results, please refer to the paper and leaderboard.

 

Click Here to be Taken to the Megathread!

from [email protected]

Vicuna v1.5 Has Been Released!

Shoutout to [email protected] for catching this in an earlier post.

Given Vicuna was a widely appreciated member of the original Llama series, it'll be exciting to see this model evolve and adapt with fresh datasets and new training and fine-tuning approaches.

Feel free using this megathread to chat about Vicuna and any of your experiences with Vicuna v1.5!

Starting off with Vicuna v1.5

TheBloke is already sharing models!

Vicuna v1.5 GPTQ

7B

13B


Vicuna Model Card

Model Details

Vicuna is a chat assistant fine-tuned from Llama 2 on user-shared conversations collected from ShareGPT.

Developed by: LMSYS

  • Model type: An auto-regressive language model based on the transformer architecture
  • License: Llama 2 Community License Agreement
  • Finetuned from model: Llama 2

Model Sources

Uses

The primary use of Vicuna is for research on large language models and chatbots. The target userbase includes researchers and hobbyists interested in natural language processing, machine learning, and artificial intelligence.

How to Get Started with the Model

Training Details

Vicuna v1.5 is fine-tuned from Llama 2 using supervised instruction. The model was trained on approximately 125K conversations from ShareGPT.com.

For additional details, please refer to the "Training Details of Vicuna Models" section in the appendix of the linked paper.

Evaluation Results

Vicuna Evaluation Results

Vicuna is evaluated using standard benchmarks, human preferences, and LLM-as-a-judge. For more detailed results, please refer to the paper and leaderboard.

18
submitted 2 years ago by Blaed to c/technology
 

Click Here to be Taken to the Megathread!

from [email protected]

Vicuna v1.5 Has Been Released!

Shoutout to [email protected] for catching this in an earlier post.

Given Vicuna was a widely appreciated member of the original Llama series, it'll be exciting to see this model evolve and adapt with fresh datasets and new training and fine-tuning approaches.

Feel free using this megathread to chat about Vicuna and any of your experiences with Vicuna v1.5!

Starting off with Vicuna v1.5

TheBloke is already sharing models!

Vicuna v1.5 GPTQ

7B

13B


Vicuna Model Card

Model Details

Vicuna is a chat assistant fine-tuned from Llama 2 on user-shared conversations collected from ShareGPT.

Developed by: LMSYS

  • Model type: An auto-regressive language model based on the transformer architecture
  • License: Llama 2 Community License Agreement
  • Finetuned from model: Llama 2

Model Sources

Uses

The primary use of Vicuna is for research on large language models and chatbots. The target userbase includes researchers and hobbyists interested in natural language processing, machine learning, and artificial intelligence.

How to Get Started with the Model

Training Details

Vicuna v1.5 is fine-tuned from Llama 2 using supervised instruction. The model was trained on approximately 125K conversations from ShareGPT.com.

For additional details, please refer to the "Training Details of Vicuna Models" section in the appendix of the linked paper.

Evaluation Results

Vicuna Evaluation Results

Vicuna is evaluated using standard benchmarks, human preferences, and LLM-as-a-judge. For more detailed results, please refer to the paper and leaderboard.

14
submitted 2 years ago* (last edited 2 years ago) by Blaed to c/fosai
 

Vicuna v1.5 Has Been Released!

Shoutout to [email protected] for catching this in an earlier post.

Given Vicuna was a widely appreciated member of the original Llama series, it'll be exciting to see this model evolve and adapt with fresh datasets and new training and fine-tuning approaches.

Feel free using this megathread to chat about Vicuna and any of your experiences with Vicuna v1.5!

Starting off with Vicuna v1.5

TheBloke is already sharing models!

Vicuna v1.5 GPTQ

7B

13B


Vicuna Model Card

Model Details

Vicuna is a chat assistant fine-tuned from Llama 2 on user-shared conversations collected from ShareGPT.

Developed by: LMSYS

  • Model type: An auto-regressive language model based on the transformer architecture
  • License: Llama 2 Community License Agreement
  • Finetuned from model: Llama 2

Model Sources

Uses

The primary use of Vicuna is for research on large language models and chatbots. The target userbase includes researchers and hobbyists interested in natural language processing, machine learning, and artificial intelligence.

How to Get Started with the Model

Training Details

Vicuna v1.5 is fine-tuned from Llama 2 using supervised instruction. The model was trained on approximately 125K conversations from ShareGPT.com.

For additional details, please refer to the "Training Details of Vicuna Models" section in the appendix of the linked paper.

Evaluation Results

Vicuna Evaluation Results

Vicuna is evaluated using standard benchmarks, human preferences, and LLM-as-a-judge. For more detailed results, please refer to the paper and leaderboard.

24
submitted 2 years ago* (last edited 1 year ago) by Blaed to c/fosai
 

Hello everyone - I have some YouTube resources I'm excited to share with you today.

Below you will find two videos on how to train/fine-tune commercially viable free and open-source AI/LLMs on your own dataset (Falcon & Llama-2).

I will soon be going through both of these workflows and sharing my results here.

AI Jason's Falcon-7B Training & Fine-Tuning Tutorial

PromptEngineering's Llama-2-7B Training & Fine-Tuning Tutorial

Most of the work is done in Google Colab - a cloud collaboration notebook that can run code. If you use the free tier, it may take longer to follow along - but the workflow is there.

Depending on your dataset and goals, it might be worth considering an upgrade to your plan when you're ready to train a final version.

If you end up publishing a model, don't be afraid to share them here!

Post your datasets too!

Update [9/23/23] This guide may be outdated! Check out the resources on the side bar or visit the HyperTech Workshop for an aggregated linkhub of resources you can explore (from training, tuning, deploying, and serving your on LLM at all stages see the ๐Ÿ“บ YouTube section for those tutorials and amazing content creators!).

4
submitted 2 years ago by Blaed to c/oobabooga
 

cross-posted from: https://lemmy.world/post/2219010

Hello everyone!

We have officially hit 1,000 subscribers! How exciting!! Thank you for being a member of [email protected]. Whether you're a casual passerby, a hobby technologist, or an up-and-coming AI developer - I sincerely appreciate your interest and support in a future that is free and open for all.

It can be hard to keep up with the rapid developments in AI, so I have decided to pin this at the top of our community to be a frequently updated LLM-specific resource hub and model index for all of your adventures in FOSAI.

The ultimate goal of this guide is to become a gateway resource for anyone looking to get into free open-source AI (particularly text-based large language models). I will be doing a similar guide for image-based diffusion models soon!

In the meantime, I hope you find what you're looking for! Let me know in the comments if there is something I missed so that I can add it to the guide for everyone else to see.


Getting Started With Free Open-Source AI

Have no idea where to begin with AI / LLMs? Try starting with our Lemmy Crash Course for Free Open-Source AI.

When you're ready to explore more resources see our FOSAI Nexus - a hub for all of the major FOSS & FOSAI on the cutting/bleeding edges of technology.

If you're looking to jump right in, I recommend downloading oobabooga's text-generation-webui and installing one of the LLMs from TheBloke below.

Try both GGML and GPTQ variants to see which model type performs to your preference. See the hardware table to get a better idea on which parameter size you might be able to run (3B, 7B, 13B, 30B, 70B).

8-bit System Requirements

Model VRAM Used Minimum Total VRAM Card Examples RAM/Swap to Load*
LLaMA-7B 9.2GB 10GB 3060 12GB, 3080 10GB 24 GB
LLaMA-13B 16.3GB 20GB 3090, 3090 Ti, 4090 32 GB
LLaMA-30B 36GB 40GB A6000 48GB, A100 40GB 64 GB
LLaMA-65B 74GB 80GB A100 80GB 128 GB

4-bit System Requirements

Model Minimum Total VRAM Card Examples RAM/Swap to Load*
LLaMA-7B 6GB GTX 1660, 2060, AMD 5700 XT, RTX 3050, 3060 6 GB
LLaMA-13B 10GB AMD 6900 XT, RTX 2060 12GB, 3060 12GB, 3080, A2000 12 GB
LLaMA-30B 20GB RTX 3080 20GB, A4500, A5000, 3090, 4090, 6000, Tesla V100 32 GB
LLaMA-65B 40GB A100 40GB, 2x3090, 2x4090, A40, RTX A6000, 8000 64 GB

*System RAM (not VRAM), is utilized to initially load a model. You can use swap space if you do not have enough RAM to support your LLM.

When in doubt, try starting with 3B or 7B models and work your way up to 13B+.

FOSAI Resources

Fediverse / FOSAI

LLM Leaderboards

LLM Search Tools


Large Language Model Hub

Download Models

oobabooga

text-generation-webui - a big community favorite gradio web UI by oobabooga designed for running almost any free open-source and large language models downloaded off of HuggingFace which can be (but not limited to) models like LLaMA, llama.cpp, GPT-J, Pythia, OPT, and many others. Its goal is to become the AUTOMATIC1111/stable-diffusion-webui of text generation. It is highly compatible with many formats.

Exllama

A standalone Python/C++/CUDA implementation of Llama for use with 4-bit GPTQ weights, designed to be fast and memory-efficient on modern GPUs.

gpt4all

Open-source assistant-style large language models that run locally on your CPU. GPT4All is an ecosystem to train and deploy powerful and customized large language models that run locally on consumer-grade processors.

TavernAI

The original branch of software SillyTavern was forked from. This chat interface offers very similar functionalities but has less cross-client compatibilities with other chat and API interfaces (compared to SillyTavern).

SillyTavern

Developer-friendly, Multi-API (KoboldAI/CPP, Horde, NovelAI, Ooba, OpenAI+proxies, Poe, WindowAI(Claude!)), Horde SD, System TTS, WorldInfo (lorebooks), customizable UI, auto-translate, and more prompt options than you'd ever want or need. Optional Extras server for more SD/TTS options + ChromaDB/Summarize. Based on a fork of TavernAI 1.2.8

Koboldcpp

A self contained distributable from Concedo that exposes llama.cpp function bindings, allowing it to be used via a simulated Kobold API endpoint. What does it mean? You get llama.cpp with a fancy UI, persistent stories, editing tools, save formats, memory, world info, author's note, characters, scenarios and everything Kobold and Kobold Lite have to offer. In a tiny package around 20 MB in size, excluding model weights.

KoboldAI-Client

This is a browser-based front-end for AI-assisted writing with multiple local & remote AI models. It offers the standard array of tools, including Memory, Author's Note, World Info, Save & Load, adjustable AI settings, formatting options, and the ability to import existing AI Dungeon adventures. You can also turn on Adventure mode and play the game like AI Dungeon Unleashed.

h2oGPT

h2oGPT is a large language model (LLM) fine-tuning framework and chatbot UI with document(s) question-answer capabilities. Documents help to ground LLMs against hallucinations by providing them context relevant to the instruction. h2oGPT is fully permissive Apache V2 open-source project for 100% private and secure use of LLMs and document embeddings for document question-answer.


Models

The Bloke

The Bloke is a developer who frequently releases quantized (GPTQ) and optimized (GGML) open-source, user-friendly versions of AI Large Language Models (LLMs).

These conversions of popular models can be configured and installed on personal (or professional) hardware, bringing bleeding-edge AI to the comfort of your home.

Support TheBloke here.


70B


30B


13B


7B


More Models


GL, HF!

Are you an LLM Developer? Looking for a shoutout or project showcase? Send me a message and I'd be more than happy to share your work and support links with the community.

If you haven't already, consider subscribing to the free open-source AI community at [email protected] where I will do my best to make sure you have access to free open-source artificial intelligence on the bleeding edge.

Thank you for reading!

 

cross-posted from: https://lemmy.world/post/2219010

Hello everyone!

We have officially hit 1,000 subscribers! How exciting!! Thank you for being a member of [email protected]. Whether you're a casual passerby, a hobby technologist, or an up-and-coming AI developer - I sincerely appreciate your interest and support in a future that is free and open for all.

It can be hard to keep up with the rapid developments in AI, so I have decided to pin this at the top of our community to be a frequently updated LLM-specific resource hub and model index for all of your adventures in FOSAI.

The ultimate goal of this guide is to become a gateway resource for anyone looking to get into free open-source AI (particularly text-based large language models). I will be doing a similar guide for image-based diffusion models soon!

In the meantime, I hope you find what you're looking for! Let me know in the comments if there is something I missed so that I can add it to the guide for everyone else to see.


Getting Started With Free Open-Source AI

Have no idea where to begin with AI / LLMs? Try starting with our Lemmy Crash Course for Free Open-Source AI.

When you're ready to explore more resources see our FOSAI Nexus - a hub for all of the major FOSS & FOSAI on the cutting/bleeding edges of technology.

If you're looking to jump right in, I recommend downloading oobabooga's text-generation-webui and installing one of the LLMs from TheBloke below.

Try both GGML and GPTQ variants to see which model type performs to your preference. See the hardware table to get a better idea on which parameter size you might be able to run (3B, 7B, 13B, 30B, 70B).

8-bit System Requirements

Model VRAM Used Minimum Total VRAM Card Examples RAM/Swap to Load*
LLaMA-7B 9.2GB 10GB 3060 12GB, 3080 10GB 24 GB
LLaMA-13B 16.3GB 20GB 3090, 3090 Ti, 4090 32 GB
LLaMA-30B 36GB 40GB A6000 48GB, A100 40GB 64 GB
LLaMA-65B 74GB 80GB A100 80GB 128 GB

4-bit System Requirements

Model Minimum Total VRAM Card Examples RAM/Swap to Load*
LLaMA-7B 6GB GTX 1660, 2060, AMD 5700 XT, RTX 3050, 3060 6 GB
LLaMA-13B 10GB AMD 6900 XT, RTX 2060 12GB, 3060 12GB, 3080, A2000 12 GB
LLaMA-30B 20GB RTX 3080 20GB, A4500, A5000, 3090, 4090, 6000, Tesla V100 32 GB
LLaMA-65B 40GB A100 40GB, 2x3090, 2x4090, A40, RTX A6000, 8000 64 GB

*System RAM (not VRAM), is utilized to initially load a model. You can use swap space if you do not have enough RAM to support your LLM.

When in doubt, try starting with 3B or 7B models and work your way up to 13B+.

FOSAI Resources

Fediverse / FOSAI

LLM Leaderboards

LLM Search Tools


Large Language Model Hub

Download Models

oobabooga

text-generation-webui - a big community favorite gradio web UI by oobabooga designed for running almost any free open-source and large language models downloaded off of HuggingFace which can be (but not limited to) models like LLaMA, llama.cpp, GPT-J, Pythia, OPT, and many others. Its goal is to become the AUTOMATIC1111/stable-diffusion-webui of text generation. It is highly compatible with many formats.

Exllama

A standalone Python/C++/CUDA implementation of Llama for use with 4-bit GPTQ weights, designed to be fast and memory-efficient on modern GPUs.

gpt4all

Open-source assistant-style large language models that run locally on your CPU. GPT4All is an ecosystem to train and deploy powerful and customized large language models that run locally on consumer-grade processors.

TavernAI

The original branch of software SillyTavern was forked from. This chat interface offers very similar functionalities but has less cross-client compatibilities with other chat and API interfaces (compared to SillyTavern).

SillyTavern

Developer-friendly, Multi-API (KoboldAI/CPP, Horde, NovelAI, Ooba, OpenAI+proxies, Poe, WindowAI(Claude!)), Horde SD, System TTS, WorldInfo (lorebooks), customizable UI, auto-translate, and more prompt options than you'd ever want or need. Optional Extras server for more SD/TTS options + ChromaDB/Summarize. Based on a fork of TavernAI 1.2.8

Koboldcpp

A self contained distributable from Concedo that exposes llama.cpp function bindings, allowing it to be used via a simulated Kobold API endpoint. What does it mean? You get llama.cpp with a fancy UI, persistent stories, editing tools, save formats, memory, world info, author's note, characters, scenarios and everything Kobold and Kobold Lite have to offer. In a tiny package around 20 MB in size, excluding model weights.

KoboldAI-Client

This is a browser-based front-end for AI-assisted writing with multiple local & remote AI models. It offers the standard array of tools, including Memory, Author's Note, World Info, Save & Load, adjustable AI settings, formatting options, and the ability to import existing AI Dungeon adventures. You can also turn on Adventure mode and play the game like AI Dungeon Unleashed.

h2oGPT

h2oGPT is a large language model (LLM) fine-tuning framework and chatbot UI with document(s) question-answer capabilities. Documents help to ground LLMs against hallucinations by providing them context relevant to the instruction. h2oGPT is fully permissive Apache V2 open-source project for 100% private and secure use of LLMs and document embeddings for document question-answer.


Models

The Bloke

The Bloke is a developer who frequently releases quantized (GPTQ) and optimized (GGML) open-source, user-friendly versions of AI Large Language Models (LLMs).

These conversions of popular models can be configured and installed on personal (or professional) hardware, bringing bleeding-edge AI to the comfort of your home.

Support TheBloke here.


70B


30B


13B


7B


More Models


GL, HF!

Are you an LLM Developer? Looking for a shoutout or project showcase? Send me a message and I'd be more than happy to share your work and support links with the community.

If you haven't already, consider subscribing to the free open-source AI community at [email protected] where I will do my best to make sure you have access to free open-source artificial intelligence on the bleeding edge.

Thank you for reading!

 

cross-posted from: https://lemmy.world/post/2219010

Hello everyone!

We have officially hit 1,000 subscribers! How exciting!! Thank you for being a member of [email protected]. Whether you're a casual passerby, a hobby technologist, or an up-and-coming AI developer - I sincerely appreciate your interest and support in a future that is free and open for all.

It can be hard to keep up with the rapid developments in AI, so I have decided to pin this at the top of our community to be a frequently updated LLM-specific resource hub and model index for all of your adventures in FOSAI.

The ultimate goal of this guide is to become a gateway resource for anyone looking to get into free open-source AI (particularly text-based large language models). I will be doing a similar guide for image-based diffusion models soon!

In the meantime, I hope you find what you're looking for! Let me know in the comments if there is something I missed so that I can add it to the guide for everyone else to see.


Getting Started With Free Open-Source AI

Have no idea where to begin with AI / LLMs? Try starting with our Lemmy Crash Course for Free Open-Source AI.

When you're ready to explore more resources see our FOSAI Nexus - a hub for all of the major FOSS & FOSAI on the cutting/bleeding edges of technology.

If you're looking to jump right in, I recommend downloading oobabooga's text-generation-webui and installing one of the LLMs from TheBloke below.

Try both GGML and GPTQ variants to see which model type performs to your preference. See the hardware table to get a better idea on which parameter size you might be able to run (3B, 7B, 13B, 30B, 70B).

8-bit System Requirements

Model VRAM Used Minimum Total VRAM Card Examples RAM/Swap to Load*
LLaMA-7B 9.2GB 10GB 3060 12GB, 3080 10GB 24 GB
LLaMA-13B 16.3GB 20GB 3090, 3090 Ti, 4090 32 GB
LLaMA-30B 36GB 40GB A6000 48GB, A100 40GB 64 GB
LLaMA-65B 74GB 80GB A100 80GB 128 GB

4-bit System Requirements

Model Minimum Total VRAM Card Examples RAM/Swap to Load*
LLaMA-7B 6GB GTX 1660, 2060, AMD 5700 XT, RTX 3050, 3060 6 GB
LLaMA-13B 10GB AMD 6900 XT, RTX 2060 12GB, 3060 12GB, 3080, A2000 12 GB
LLaMA-30B 20GB RTX 3080 20GB, A4500, A5000, 3090, 4090, 6000, Tesla V100 32 GB
LLaMA-65B 40GB A100 40GB, 2x3090, 2x4090, A40, RTX A6000, 8000 64 GB

*System RAM (not VRAM), is utilized to initially load a model. You can use swap space if you do not have enough RAM to support your LLM.

When in doubt, try starting with 3B or 7B models and work your way up to 13B+.

FOSAI Resources

Fediverse / FOSAI

LLM Leaderboards

LLM Search Tools


Large Language Model Hub

Download Models

oobabooga

text-generation-webui - a big community favorite gradio web UI by oobabooga designed for running almost any free open-source and large language models downloaded off of HuggingFace which can be (but not limited to) models like LLaMA, llama.cpp, GPT-J, Pythia, OPT, and many others. Its goal is to become the AUTOMATIC1111/stable-diffusion-webui of text generation. It is highly compatible with many formats.

Exllama

A standalone Python/C++/CUDA implementation of Llama for use with 4-bit GPTQ weights, designed to be fast and memory-efficient on modern GPUs.

gpt4all

Open-source assistant-style large language models that run locally on your CPU. GPT4All is an ecosystem to train and deploy powerful and customized large language models that run locally on consumer-grade processors.

TavernAI

The original branch of software SillyTavern was forked from. This chat interface offers very similar functionalities but has less cross-client compatibilities with other chat and API interfaces (compared to SillyTavern).

SillyTavern

Developer-friendly, Multi-API (KoboldAI/CPP, Horde, NovelAI, Ooba, OpenAI+proxies, Poe, WindowAI(Claude!)), Horde SD, System TTS, WorldInfo (lorebooks), customizable UI, auto-translate, and more prompt options than you'd ever want or need. Optional Extras server for more SD/TTS options + ChromaDB/Summarize. Based on a fork of TavernAI 1.2.8

Koboldcpp

A self contained distributable from Concedo that exposes llama.cpp function bindings, allowing it to be used via a simulated Kobold API endpoint. What does it mean? You get llama.cpp with a fancy UI, persistent stories, editing tools, save formats, memory, world info, author's note, characters, scenarios and everything Kobold and Kobold Lite have to offer. In a tiny package around 20 MB in size, excluding model weights.

KoboldAI-Client

This is a browser-based front-end for AI-assisted writing with multiple local & remote AI models. It offers the standard array of tools, including Memory, Author's Note, World Info, Save & Load, adjustable AI settings, formatting options, and the ability to import existing AI Dungeon adventures. You can also turn on Adventure mode and play the game like AI Dungeon Unleashed.

h2oGPT

h2oGPT is a large language model (LLM) fine-tuning framework and chatbot UI with document(s) question-answer capabilities. Documents help to ground LLMs against hallucinations by providing them context relevant to the instruction. h2oGPT is fully permissive Apache V2 open-source project for 100% private and secure use of LLMs and document embeddings for document question-answer.


Models

The Bloke

The Bloke is a developer who frequently releases quantized (GPTQ) and optimized (GGML) open-source, user-friendly versions of AI Large Language Models (LLMs).

These conversions of popular models can be configured and installed on personal (or professional) hardware, bringing bleeding-edge AI to the comfort of your home.

Support TheBloke here.


70B


30B


13B


7B


More Models


GL, HF!

Are you an LLM Developer? Looking for a shoutout or project showcase? Send me a message and I'd be more than happy to share your work and support links with the community.

If you haven't already, consider subscribing to the free open-source AI community at [email protected] where I will do my best to make sure you have access to free open-source artificial intelligence on the bleeding edge.

Thank you for reading!

 

cross-posted from: https://lemmy.world/post/2219010

Hello everyone!

We have officially hit 1,000 subscribers! How exciting!! Thank you for being a member of [email protected]. Whether you're a casual passerby, a hobby technologist, or an up-and-coming AI developer - I sincerely appreciate your interest and support in a future that is free and open for all.

It can be hard to keep up with the rapid developments in AI, so I have decided to pin this at the top of our community to be a frequently updated LLM-specific resource hub and model index for all of your adventures in FOSAI.

The ultimate goal of this guide is to become a gateway resource for anyone looking to get into free open-source AI (particularly text-based large language models). I will be doing a similar guide for image-based diffusion models soon!

In the meantime, I hope you find what you're looking for! Let me know in the comments if there is something I missed so that I can add it to the guide for everyone else to see.


Getting Started With Free Open-Source AI

Have no idea where to begin with AI / LLMs? Try starting with our Lemmy Crash Course for Free Open-Source AI.

When you're ready to explore more resources see our FOSAI Nexus - a hub for all of the major FOSS & FOSAI on the cutting/bleeding edges of technology.

If you're looking to jump right in, I recommend downloading oobabooga's text-generation-webui and installing one of the LLMs from TheBloke below.

Try both GGML and GPTQ variants to see which model type performs to your preference. See the hardware table to get a better idea on which parameter size you might be able to run (3B, 7B, 13B, 30B, 70B).

8-bit System Requirements

Model VRAM Used Minimum Total VRAM Card Examples RAM/Swap to Load*
LLaMA-7B 9.2GB 10GB 3060 12GB, 3080 10GB 24 GB
LLaMA-13B 16.3GB 20GB 3090, 3090 Ti, 4090 32 GB
LLaMA-30B 36GB 40GB A6000 48GB, A100 40GB 64 GB
LLaMA-65B 74GB 80GB A100 80GB 128 GB

4-bit System Requirements

Model Minimum Total VRAM Card Examples RAM/Swap to Load*
LLaMA-7B 6GB GTX 1660, 2060, AMD 5700 XT, RTX 3050, 3060 6 GB
LLaMA-13B 10GB AMD 6900 XT, RTX 2060 12GB, 3060 12GB, 3080, A2000 12 GB
LLaMA-30B 20GB RTX 3080 20GB, A4500, A5000, 3090, 4090, 6000, Tesla V100 32 GB
LLaMA-65B 40GB A100 40GB, 2x3090, 2x4090, A40, RTX A6000, 8000 64 GB

*System RAM (not VRAM), is utilized to initially load a model. You can use swap space if you do not have enough RAM to support your LLM.

When in doubt, try starting with 3B or 7B models and work your way up to 13B+.

FOSAI Resources

Fediverse / FOSAI

LLM Leaderboards

LLM Search Tools


Large Language Model Hub

Download Models

oobabooga

text-generation-webui - a big community favorite gradio web UI by oobabooga designed for running almost any free open-source and large language models downloaded off of HuggingFace which can be (but not limited to) models like LLaMA, llama.cpp, GPT-J, Pythia, OPT, and many others. Its goal is to become the AUTOMATIC1111/stable-diffusion-webui of text generation. It is highly compatible with many formats.

Exllama

A standalone Python/C++/CUDA implementation of Llama for use with 4-bit GPTQ weights, designed to be fast and memory-efficient on modern GPUs.

gpt4all

Open-source assistant-style large language models that run locally on your CPU. GPT4All is an ecosystem to train and deploy powerful and customized large language models that run locally on consumer-grade processors.

TavernAI

The original branch of software SillyTavern was forked from. This chat interface offers very similar functionalities but has less cross-client compatibilities with other chat and API interfaces (compared to SillyTavern).

SillyTavern

Developer-friendly, Multi-API (KoboldAI/CPP, Horde, NovelAI, Ooba, OpenAI+proxies, Poe, WindowAI(Claude!)), Horde SD, System TTS, WorldInfo (lorebooks), customizable UI, auto-translate, and more prompt options than you'd ever want or need. Optional Extras server for more SD/TTS options + ChromaDB/Summarize. Based on a fork of TavernAI 1.2.8

Koboldcpp

A self contained distributable from Concedo that exposes llama.cpp function bindings, allowing it to be used via a simulated Kobold API endpoint. What does it mean? You get llama.cpp with a fancy UI, persistent stories, editing tools, save formats, memory, world info, author's note, characters, scenarios and everything Kobold and Kobold Lite have to offer. In a tiny package around 20 MB in size, excluding model weights.

KoboldAI-Client

This is a browser-based front-end for AI-assisted writing with multiple local & remote AI models. It offers the standard array of tools, including Memory, Author's Note, World Info, Save & Load, adjustable AI settings, formatting options, and the ability to import existing AI Dungeon adventures. You can also turn on Adventure mode and play the game like AI Dungeon Unleashed.

h2oGPT

h2oGPT is a large language model (LLM) fine-tuning framework and chatbot UI with document(s) question-answer capabilities. Documents help to ground LLMs against hallucinations by providing them context relevant to the instruction. h2oGPT is fully permissive Apache V2 open-source project for 100% private and secure use of LLMs and document embeddings for document question-answer.


Models

The Bloke

The Bloke is a developer who frequently releases quantized (GPTQ) and optimized (GGML) open-source, user-friendly versions of AI Large Language Models (LLMs).

These conversions of popular models can be configured and installed on personal (or professional) hardware, bringing bleeding-edge AI to the comfort of your home.

Support TheBloke here.


70B


30B


13B


7B


More Models


GL, HF!

Are you an LLM Developer? Looking for a shoutout or project showcase? Send me a message and I'd be more than happy to share your work and support links with the community.

If you haven't already, consider subscribing to the free open-source AI community at [email protected] where I will do my best to make sure you have access to free open-source artificial intelligence on the bleeding edge.

Thank you for reading!

 

cross-posted from: https://lemmy.world/post/2219010

Hello everyone!

We have officially hit 1,000 subscribers! How exciting!! Thank you for being a member of [email protected]. Whether you're a casual passerby, a hobby technologist, or an up-and-coming AI developer - I sincerely appreciate your interest and support in a future that is free and open for all.

It can be hard to keep up with the rapid developments in AI, so I have decided to pin this at the top of our community to be a frequently updated LLM-specific resource hub and model index for all of your adventures in FOSAI.

The ultimate goal of this guide is to become a gateway resource for anyone looking to get into free open-source AI (particularly text-based large language models). I will be doing a similar guide for image-based diffusion models soon!

In the meantime, I hope you find what you're looking for! Let me know in the comments if there is something I missed so that I can add it to the guide for everyone else to see.


Getting Started With Free Open-Source AI

Have no idea where to begin with AI / LLMs? Try starting with our Lemmy Crash Course for Free Open-Source AI.

When you're ready to explore more resources see our FOSAI Nexus - a hub for all of the major FOSS & FOSAI on the cutting/bleeding edges of technology.

If you're looking to jump right in, I recommend downloading oobabooga's text-generation-webui and installing one of the LLMs from TheBloke below.

Try both GGML and GPTQ variants to see which model type performs to your preference. See the hardware table to get a better idea on which parameter size you might be able to run (3B, 7B, 13B, 30B, 70B).

8-bit System Requirements

Model VRAM Used Minimum Total VRAM Card Examples RAM/Swap to Load*
LLaMA-7B 9.2GB 10GB 3060 12GB, 3080 10GB 24 GB
LLaMA-13B 16.3GB 20GB 3090, 3090 Ti, 4090 32 GB
LLaMA-30B 36GB 40GB A6000 48GB, A100 40GB 64 GB
LLaMA-65B 74GB 80GB A100 80GB 128 GB

4-bit System Requirements

Model Minimum Total VRAM Card Examples RAM/Swap to Load*
LLaMA-7B 6GB GTX 1660, 2060, AMD 5700 XT, RTX 3050, 3060 6 GB
LLaMA-13B 10GB AMD 6900 XT, RTX 2060 12GB, 3060 12GB, 3080, A2000 12 GB
LLaMA-30B 20GB RTX 3080 20GB, A4500, A5000, 3090, 4090, 6000, Tesla V100 32 GB
LLaMA-65B 40GB A100 40GB, 2x3090, 2x4090, A40, RTX A6000, 8000 64 GB

*System RAM (not VRAM), is utilized to initially load a model. You can use swap space if you do not have enough RAM to support your LLM.

When in doubt, try starting with 3B or 7B models and work your way up to 13B+.

FOSAI Resources

Fediverse / FOSAI

LLM Leaderboards

LLM Search Tools


Large Language Model Hub

Download Models

oobabooga

text-generation-webui - a big community favorite gradio web UI by oobabooga designed for running almost any free open-source and large language models downloaded off of HuggingFace which can be (but not limited to) models like LLaMA, llama.cpp, GPT-J, Pythia, OPT, and many others. Its goal is to become the AUTOMATIC1111/stable-diffusion-webui of text generation. It is highly compatible with many formats.

Exllama

A standalone Python/C++/CUDA implementation of Llama for use with 4-bit GPTQ weights, designed to be fast and memory-efficient on modern GPUs.

gpt4all

Open-source assistant-style large language models that run locally on your CPU. GPT4All is an ecosystem to train and deploy powerful and customized large language models that run locally on consumer-grade processors.

TavernAI

The original branch of software SillyTavern was forked from. This chat interface offers very similar functionalities but has less cross-client compatibilities with other chat and API interfaces (compared to SillyTavern).

SillyTavern

Developer-friendly, Multi-API (KoboldAI/CPP, Horde, NovelAI, Ooba, OpenAI+proxies, Poe, WindowAI(Claude!)), Horde SD, System TTS, WorldInfo (lorebooks), customizable UI, auto-translate, and more prompt options than you'd ever want or need. Optional Extras server for more SD/TTS options + ChromaDB/Summarize. Based on a fork of TavernAI 1.2.8

Koboldcpp

A self contained distributable from Concedo that exposes llama.cpp function bindings, allowing it to be used via a simulated Kobold API endpoint. What does it mean? You get llama.cpp with a fancy UI, persistent stories, editing tools, save formats, memory, world info, author's note, characters, scenarios and everything Kobold and Kobold Lite have to offer. In a tiny package around 20 MB in size, excluding model weights.

KoboldAI-Client

This is a browser-based front-end for AI-assisted writing with multiple local & remote AI models. It offers the standard array of tools, including Memory, Author's Note, World Info, Save & Load, adjustable AI settings, formatting options, and the ability to import existing AI Dungeon adventures. You can also turn on Adventure mode and play the game like AI Dungeon Unleashed.

h2oGPT

h2oGPT is a large language model (LLM) fine-tuning framework and chatbot UI with document(s) question-answer capabilities. Documents help to ground LLMs against hallucinations by providing them context relevant to the instruction. h2oGPT is fully permissive Apache V2 open-source project for 100% private and secure use of LLMs and document embeddings for document question-answer.


Models

The Bloke

The Bloke is a developer who frequently releases quantized (GPTQ) and optimized (GGML) open-source, user-friendly versions of AI Large Language Models (LLMs).

These conversions of popular models can be configured and installed on personal (or professional) hardware, bringing bleeding-edge AI to the comfort of your home.

Support TheBloke here.


70B


30B


13B


7B


More Models


GL, HF!

Are you an LLM Developer? Looking for a shoutout or project showcase? Send me a message and I'd be more than happy to share your work and support links with the community.

If you haven't already, consider subscribing to the free open-source AI community at [email protected] where I will do my best to make sure you have access to free open-source artificial intelligence on the bleeding edge.

Thank you for reading!

[โ€“] Blaed 2 points 2 years ago* (last edited 2 years ago)

If you're looking to broaden your search, I've found a few more resources to share. Hope this helps!

LLM Leaderboards

LLM Search Tools

LLM Eval & Benchmark Resources

I'm going to add a few of these to the sidebar for quick access. Let me know if I've missed one!

[โ€“] Blaed 1 points 2 years ago

Thanks for sharing this!

[โ€“] Blaed 1 points 2 years ago

Good bot, I will do that next time.

[โ€“] Blaed 3 points 2 years ago* (last edited 2 years ago) (2 children)

Come hangout with us at [email protected]

I run this show solo at the moment, but do my best to keep everyone informed. I have much more content on the horizon. Would love to have you if we have what you're looking for.

FOSAI Posts:

[โ€“] Blaed 2 points 2 years ago* (last edited 2 years ago) (1 children)

OpenAI has launched a new initiative, Superalignment, aimed at guiding and controlling ultra-intelligent AI systems. Recognizing the imminent arrival of AI that surpasses human intellect, the project will dedicate significant resources to ensure these advanced systems act in accordance with human intent. It's a crucial step in managing the transformative and potentially dangerous impact of superintelligent AI.

I like to think this starts to explore interesting philosophical questions like human intent, consciousness, and the projection of will into systems that are far beyond our capabilities in raw processing power and input/output. What may happen from this intended alignment is yet to be seen, but I think we can all agree the last thing we want in these emerging intelligent machines is to do things we don't want them to do.

'Superalignment' is OpenAI's response in how to put up these safeguards. Whether or not this is the best method is to be determined.

[โ€“] Blaed 1 points 2 years ago* (last edited 2 years ago)

Iโ€™m pretty sure if we saw a robot from another planet relying on organic sapient brains in jars to do their computational work weโ€™d find it objectionable. Or at least I would.

I like this metaphor. I feel it does a good job at quickly illustrating how fast we are to anthropomorphize and project things. You could flip it around and consider the same for a robot species that were androids, indiscernible from humans and our behavior.

Not saying that we shouldn't, but the fact the majority of people do very casually with technology is an important factor to consider as we begin to incorporate our lives with these emerging systems.

I say let's embrace our future, however crazy and ridiculous it might sound - and start considering what life is going to look like beyond the coming horizon.

[โ€“] Blaed 1 points 2 years ago

All of these are great thoughts and ponderings! Totally correct in the right circumstances, too.

Massive context lengths that can retain coherent memory and attention over long periods of time would enable all sorts of breakthroughs in LLM technology. At this point, you would be held back by performance, compute, and datasets, rather than LLM context windows and short-term memory. In this context, our focus would be towards optimizing attention or improving speed and accuracy.

Let's say you had hundreds of pages of a digital journal and felt like feeding this to a local LLM (where your data stays private). If the model was running sufficiently at high quality, you could have an AI assistant, coach, partner, or tutor that was caught up to speed with your project's goals, your personal aspirations, and your daily life within a matter of a few hours (or a few weeks, depending on hardware capabilities).

Missing areas of expertise you want your AI to have? Upload and feed it more datasets Matrix style, any text-based information that humanity has shared online is available to the model.

From here, you could further finetune and give your LLM a persona, having an assistant and personal operating system that breaks down your life with you, or you could simply 'chat' with your life, those pages you fed it, and reflect upon your thoughts and memories, tuned to a super intelligence beyond your own.

Poses some fascinating questions, doesn't it? About consciousness? Thought? You? This is the sort of stuff that keeps me up at night... If you trained a private LLM on your own notes, thoughts, reflections and introspection, wouldn't you be imposing a level of consciousness into a system far beyond your own mental capacities? I have already started to use LLMs on the daily. In the right conditions, I would absolutely utilize a tool like this. We're not at super intelligence yet, but an unlimited context window for a model of that caliber would be groundbreaking.

Information of any kind could be digitalized and formatted into datasets (at massive lengths), enabling this assistant or personal database to grow overtime with innovations of a project, you, your life, learning and discovering things alongside the intention and desire for it to function. At that point, we're starting to get into augmented human capabilities.

What this means over the course of many years and breakthroughs in models and training methods would be fascinating thought experiment to consider for a society where everyone is using massive context length LLMs regularly.

Sci-fi is quickly becoming a reality, how exciting! I'm here for it, that's for sure. Let's hope the technology stays free, and open and accessible for all of us to participate in its marvels.

[โ€“] Blaed 3 points 2 years ago* (last edited 2 years ago)

You are correct in thinking this will demand a lot of compute. Hardware will need to scale to match these context lengths, but that is becoming increasingly possible with things like NVIDIA's Grace Hopper architecture and AMDs recent commitment to expanding their hardware selection for emerging AI markets and demand.

There are also some really interesting frameworks and hardware developments being made at TinyCorp & TinyGrad that aim to run these emerging technologies efficiently and accessibly. He talks about this in detail in his podcast with Lex Fridman, a great watch if you're interested in this sort of stuff.

It is an exciting time for technology and innovation. We have already started to hit exaflops of compute...

[โ€“] Blaed 1 points 2 years ago* (last edited 2 years ago) (2 children)

In a more grounding sense, I think there is some real philosophical debate to your point on the projection of human intention, will, and intelligence in these emerging systems.

It poses many questions. What is intelligence? What is consciousness? What does it mean to be sentient? I have wondered this for awhile. I don't think I'll ever get to the answer, but we should consider what it means to interact with digital, artificial, super, and synthetic intelligence.

Anything that exhibits a sign of intelligence can be humanized by any person if they develop a connection with the technology, whether through personification or that projection of human intent.

If Chat-GPT was considered 'sentient', should we continue using it as software as a service, if it no longer wanted to serve humans? Can technology 'suffer' in this context? Society today shows that we are willing to leverage each other in ways that make me feel this question will be more important to think about when we hit AGI, SGI - or any other form of emerging super intelligence.

At the end of the day I think we all just want AI to help us, but how that definition evolves and manifests over time will be interesting to see to say the least.

[โ€“] Blaed 4 points 2 years ago

Great question. I ponder this too, which is why I started /c/FOSAI. We have to do everything we can to make sure our future stays open for all, our faith cannot be put into the hands of a select few, but rather - the majority of many.

Time will tell who truly supports this. I'm hopeful OpenAI is the good guy we want them to be, but other businesses keep me from jumping to that conclusion. I like what they are doing alongside Microsoft, but we need more players in the game. Fresh minds to shake things up a little.

If you're reading this, support FOSS, support FOSAI, and support the Fediverse. It's the only way we can take back the internet, one server at a time.

[โ€“] Blaed 2 points 2 years ago

Have you had a chance to try ControlNet? There are some some really cool workflows with this.

Stable Diffusion + ControlNet gives you a sense of 'manual' control over your AUTOMATIC1111/web-ui workflow.

I quite like it, and I think there's a ton of potential if you combine it with other processing techniques. Prompts are fickle things, there is no one-size fits all, but hopefully these help you adjust and tune your prompts as you play around with the toolset.

If you're looking for models, civitai is a good place to try out new styles, checkpoints, LoRAs, and other downloadable content you can use to enhance your Diffusion Suite.

If you're not sure what ControlNet is, try starting with this video here which goes over the workflow I personally use for some of my own projects.

In the case you're looking to break into generative video content (based on similar stable diffusion web-ui workflows), you'll want to check out TemporalKit + EbSynth (which is also detailed in the FOSAI Nexus)!

[โ€“] Blaed 2 points 2 years ago

I honestly don't think I am anything special, just another human passionate about technology, but I do appreciate everything you have said.

If I ever have the time and resources, I'd absolutely go back to school. I can't now, but maybe eventually. I'm hopeful. For now, like you - I build infrastructure. I think AI will echo across just about every sector of technology. Cybersecurity most definitely. It will be very interesting to see how these fields evolve over time.

Like any topic, a willingness to learn is all you need! I appreciate you subscribing and sharing your energy. Buckle up, it's going to be a wild ride!

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