Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

[Tracking] New Model Requests #692

Closed
4 of 11 tasks
CharlieFRuan opened this issue Aug 8, 2023 · 9 comments
Closed
4 of 11 tasks

[Tracking] New Model Requests #692

CharlieFRuan opened this issue Aug 8, 2023 · 9 comments
Labels
status: tracking Tracking work in progress

Comments

@CharlieFRuan
Copy link
Contributor

CharlieFRuan commented Aug 8, 2023

Overview

This is a tracker for all new model requests from the community. The end goal is to have prebuilt models for all these models (either from us, or from the community -- see below).

Help Wanted

We would really appreciate it if you could contribute to the project by compiling any requested model listed below.

You could:

  1. Follow the detailed steps listed in this Python notebook (runnable in Colab)
  2. Upload your compiled model to your huggingface repo (also covered in the notebook)
  3. Post the link to your huggingface repo below so that others may benefit from your great work!

For more information (e.g. what architectures are currently supported) see: https://mlc.ai/mlc-llm/docs/prebuilt_models.html

To see what prebuilt models we currently have: https://huggingface.co/mlc-ai

Thank you!

Models with Supported Architecture

Models with Unsupported Architecture

Others

@acalatrava
Copy link
Contributor

acalatrava commented Aug 9, 2023

Model: https://huggingface.co/Tap-M/Luna-AI-Llama2-Uncensored

Repo: https://huggingface.co/acalatrava/mlc-chat-luna-ai-llama2-7b-chat-uncensored-q3f16_1

@MrJungle1
Copy link

@CharlieFRuan I am very happy to contribute my code, but I need some information to get started. Can you provide some more information or documents?

@CharlieFRuan
Copy link
Contributor Author

@MrJungle1 Hi, thank you for the interest! Documentation can be found here: https://llm.mlc.ai/docs/

Specifically, compiling models can be located here: https://llm.mlc.ai/docs/compilation/compile_models.html

@MrJungle1
Copy link

MrJungle1 commented Dec 11, 2023

@CharlieFRuan Hello, thank you for your reply. I read this doc, but I don’t seem to find what I want. If I want to support a new model_type, such as "model_type": "qwen", where should I start? Or as you say, a new model architecture.

@CharlieFRuan
Copy link
Contributor Author

CharlieFRuan commented Dec 11, 2023

Ahh I see! We are currently migrating to a new workflow, and documentation should be up soon (this week probably). Meanwhile, you could refer to #1408 which adds support for GPT-NeoX. Adding a new model should be similar. The commands to use in this new workflow (for now, since it is not officially supported yet) is:

  • python -m mlc_chat gen_config dist/models/Llama-2-7b-chat-hf --quantization q4f16_1 -o ./dist/llama_q4f16/params --conv-template llama-2
  • python -m mlc_chat compile ./dist/llama_q4f16/params/mlc-chat-config.json -o ./dist/llama_q4f16/llama_q4f16.so
  • python -m mlc_chat convert_weight dist/models/Llama-2-7b-chat-hf --quantization q4f16_1 -o ./dist/llama_q4f16/params/

Then you can use the same steps as before to run the model in runtime.

Made a tracker for the new workflow here: #1420; we will add a Colab tutorial on adding new models.

@MrJungle1
Copy link

Great, thank you for your reply, LGTM!

@niutech
Copy link

niutech commented Dec 18, 2023

Could you please add Microsoft Phi-1.5 and Phi-2 to the list (#905)? Thanks.

@CharlieFRuan
Copy link
Contributor Author

@CharlieFRuan
Copy link
Contributor Author

Replacing this page with https://github.com/orgs/mlc-ai/projects/2. Submit a request to the dashboard following #1042

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
status: tracking Tracking work in progress
Projects
Status: Done
Development

No branches or pull requests

4 participants