| --- |
| license: mit |
| --- |
| # cvx-coder |
|
|
| ## Introduction |
|
|
| cvx-coder aims to improve the Matlab [CVX](https://cvxr.com/cvx) code ability and QA ability of LLMs. It is a [phi-3 model](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) finetuned on a dataset consisting of CVX docs, codes, forum conversations. |
|
|
| ## Quickstart |
| Run the following: |
| ```python |
| from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline |
| m_path="tim1900/cvx-coder" |
| model = AutoModelForCausalLM.from_pretrained( |
| m_path, |
| device_map="cuda", |
| torch_dtype="auto", |
| trust_remote_code=True, |
| ) |
| tokenizer = AutoTokenizer.from_pretrained(m_path) |
| pipe = pipeline( |
| "text-generation", |
| model=model, |
| tokenizer=tokenizer, |
| ) |
| generation_args = { |
| "max_new_tokens": 2000, |
| "return_full_text": False, |
| "temperature": 0, |
| "do_sample": False, |
| } |
| content='''my problem is not convex, can i use cvx? if not, what should i do, be specific.''' |
| messages = [ |
| {"role": "user", "content": content}, |
| ] |
| output = pipe(messages, **generation_args) |
| print(output[0]['generated_text']) |
| ``` |