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Kimi-Dev-72B

Text Generation
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Safetensors
qwen2
code
swebench
software
issue-resolving
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text-generation-inference
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LICENSE.md ADDED
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+ - Kimi-Dev-72B is built with Qwen-2.5-72B. Qwen-2.5-72B is licensed under the [Qwen LICENSE AGREEMENT](https://huggingface.co/Qwen/Qwen2.5-72B/blob/main/LICENSE), Copyright (c) Alibaba Cloud. All Rights Reserved.
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+ - Subject to the Qwen LICENSE AGREEMENT, Kimi-Dev-72B is under MIT license.
README.md ADDED
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+ ---
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+ license: mit
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+ base_model:
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+ - Qwen/Qwen2.5-72B
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+ tags:
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+ - code
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+ - swebench
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+ - software
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+ - issue-resolving
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+ ---
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+ <!-- # Kimi-Dev -->
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+
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+ <div align="center">
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+ <img src="./assets/main_logo.png" alt="Kimi Logo" width="400" />
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+ <h2><a href="https://moonshotai.github.io/Kimi-Dev/">
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+ Introducing Kimi-Dev: <br>A Strong and Open-source Coding LLM for Issue Resolution</a></h2>
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+ </a></h2>
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+ <b>Kimi-Dev Team</b>
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+ <br>
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+
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+ </div>
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+ <div align="center">
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+ <a href="">
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+ <b>📄 Tech Report (Coming soon...)</b>
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+ </a> &nbsp;|&nbsp;
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+ <a href="https://github.com/MoonshotAI/Kimi-Dev">
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+ <b>📄 Github</b>
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+ </a> &nbsp;
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+ </div>
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+
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+ <br>
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+ <br>
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+
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+ <!-- https://github.com/MoonshotAI/Kimi-Dev -->
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+
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+ We introduce Kimi-Dev-72B, our new open-source coding LLM for software engineering tasks. Kimi-Dev-72B achieves a new state-of-the-art on SWE-bench Verified among open-source models.
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+
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+ - Kimi-Dev-72B achieves 60.4% performance on SWE-bench Verified. It surpasses the runner-up, setting a new state-of-the-art result among open-source models.
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+
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+
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+ - Kimi-Dev-72B is optimized via large-scale reinforcement learning. It autonomously patches real repositories in Docker and gains rewards only when the entire test suite passes. This ensures correct and robust solutions, aligning with real-world development standards.
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+
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+
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+ - Kimi-Dev-72B is available for download and deployment on Hugging Face and GitHub. We welcome developers and researchers to explore its capabilities and contribute to development.
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+
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+
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+ <div align="center">
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+ <img src="./assets/open_performance_white.png" alt="Kimi Logo" width="600" />
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+ <p><b>Performance of Open-source Models on SWE-bench Verified.</b></p>
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+
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+ </div>
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+
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+
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+
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+ ## Quick Start
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+ ```
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+ model_name = "moonshotai/Kimi-Dev-72B"
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+
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+ model = AutoModelForCausalLM.from_pretrained(
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+ model_name,
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+ torch_dtype="auto",
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+ device_map="auto"
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+ )
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+ tokenizer = AutoTokenizer.from_pretrained(model_name)
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+
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+ prompt = "Give me a short introduction to large language model."
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+ messages = [
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+ {"role": "system", "content": "You are a helpful assistant."},
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+ {"role": "user", "content": prompt}
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+ ]
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+ text = tokenizer.apply_chat_template(
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+ messages,
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+ tokenize=False,
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+ add_generation_prompt=True
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+ )
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+ model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
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+
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+ generated_ids = model.generate(
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+ **model_inputs,
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+ max_new_tokens=512
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+ )
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+ generated_ids = [
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+ output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
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+ ]
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+
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+ response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
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+
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+ ```
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+
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+ ## Citation
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+ ```
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+ @misc{kimi_dev_72b_2025,
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+ title = {Introducing Kimi-Dev: A Strong and Open-source Coding LLM for Issue Resolution},
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+ author = {{Kimi-Dev Team}},
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+ year = {2025},
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+ month = {June},
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+ url = {\url{https://www.moonshot.cn/Kimi-Dev}}
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+ }
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+ ```
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