--- language: - en pipeline_tag: text-generation tags: - code ---

OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement

OpenCodeInterpreter

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## Introduction OpenCodeInterpreter is a family of open-source code generation systems designed to bridge the gap between large language models and advanced proprietary systems like the GPT-4 Code Interpreter. It significantly advances code generation capabilities by integrating execution and iterative refinement functionalities. For further information and related work, refer to our paper: ["OpenCodeInterpreter: A System for Enhanced Code Generation and Execution"](https://arxiv.org/abs/2402.14658) available on arXiv. ## Model Information This model is based on [deepseek-coder-33b-base](https://huggingface.co/deepseek-ai/deepseek-coder-33b-base). ## Model Usage ### Inference ```python import torch from transformers import AutoTokenizer, AutoModelForCausalLM model_path="m-a-p/OpenCodeInterpreter-DS-33B" tokenizer = AutoTokenizer.from_pretrained(model_path) model = AutoModelForCausalLM.from_pretrained( model_path, torch_dtype=torch.bfloat16, device_map="auto", ) model.eval() prompt = "Write a function to find the shared elements from the given two lists." inputs = tokenizer.apply_chat_template( [{'role': 'user', 'content': prompt }], return_tensors="pt" ).to(model.device) outputs = model.generate( inputs, max_new_tokens=1024, do_sample=False, pad_token_id=tokenizer.eos_token_id, eos_token_id=tokenizer.eos_token_id, ) print(tokenizer.decode(outputs[0][len(inputs[0]):], skip_special_tokens=True)) ``` ## Contact If you have any inquiries, please feel free to raise an issue or reach out to us via email at: xiangyue.work@gmail.com, zhengtianyu0428@gmail.com. We're here to assist you!"