--- base_model: - deepseek-ai/deepseek-coder-6.7b-base library_name: transformers --- # CAC-v0.1 CAC is a large language model with 6.7B parameters specifically finetuned for code completions. CAC, although trained for code autocompletion, can also be used for other code related tasks such as: - Generation - Summarization - Translation - Question Answering - Optimization - Debugging - Code Review and more. --- This is the very first version of CAC (0.1) and is still under development. For this version, we chose to go ahead with DeepSeek-Coder-6.7B as the base model. --- ## Model Details - Training Data: Exclusively fine-tuned on a proprietary dataset of 1.8 billion tokens of high-quality programming problems and solutions. - The dataset was generated manually and is internal to CodeMate. - Training Techniques: The model was fine-tuned using Flash Attention 2, trained over 15 hours on 40 A100-80GB GPUs. - A sequence length of 8096 tokens was used during training. - Multilingual Support: CAC-v0.1 is proficient in multiple programming languages, including Python, C/C++, TypeScript, Java, and more. --- ## Load the model with Transformers: Make sure to install Transformers from the main git branch: ``` pip install git+https://github.com/huggingface/transformers.git ``` #### How to Prompt the Model: This model accepts prompts in the Alpaca/Vicuna instruction format. For example: ``` ### System Prompt You are an intelligent programming assistant. ### User Message Implement a linked list in C++ ### Assistant ... ``` You can also use the Mistral chat template for conversations: ``` [INST] .... [/INST] ... ``` #### Load the model: ``` from transformers import AutoTokenizer, AutoModelForCausalLM # Initialize the model model_path = "codemateai/CodeMate-v0.1" model = AutoModelForCausalLM.from_pretrained(model_path, device_map="auto") tokenizer = AutoTokenizer.from_pretrained(model_path) # ... generate response ... ``` --- ## Limitations This model has undergone very limited testing. CodeMate recommends additional safety testing before any real-world deployments. For more information and updates, visit the [CodeMate website](https://codemate.ai).