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+ deepseek-coder-7b-instruct-v1.5-Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
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+ deepseek-coder-7b-instruct-v1.5-Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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+ deepseek-coder-7b-instruct-v1.5-Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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+ deepseek-coder-7b-instruct-v1.5-Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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+ deepseek-coder-7b-instruct-v1.5-Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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+ deepseek-coder-7b-instruct-v1.5-Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
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+ deepseek-coder-7b-instruct-v1.5-Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
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LICENSE ADDED
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README.md ADDED
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+ ---
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+ license: other
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+ license_name: deepseek
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+ license_link: LICENSE
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+ ---
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+
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+ <p align="center">
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+ <img width="1000px" alt="DeepSeek Coder" src="https://github.com/deepseek-ai/DeepSeek-Coder/blob/main/pictures/logo.png?raw=true">
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+ </p>
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+ <p align="center"><a href="https://www.deepseek.com/">[🏠Homepage]</a> | <a href="https://coder.deepseek.com/">[🤖 Chat with DeepSeek Coder]</a> | <a href="https://discord.gg/Tc7c45Zzu5">[Discord]</a> | <a href="https://github.com/guoday/assert/blob/main/QR.png?raw=true">[Wechat(微信)]</a> </p>
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+ <hr>
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+
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+
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+
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+
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+ ### 1. Introduction of Deepseek-Coder-7B-Instruct v1.5
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+
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+ Deepseek-Coder-7B-Instruct-v1.5 is continue pre-trained from Deepseek-LLM 7B on 2T tokens by employing a window size of 4K and next token prediction objective, and then fine-tuned on 2B tokens of instruction data.
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+
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+ - **Home Page:** [DeepSeek](https://deepseek.com/)
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+ - **Repository:** [deepseek-ai/deepseek-coder](https://github.com/deepseek-ai/deepseek-coder)
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+ - **Chat With DeepSeek Coder:** [DeepSeek-Coder](https://coder.deepseek.com/)
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+
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+
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+ ### 2. How to Use
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+ Here give some examples of how to use our model.
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+ #### Chat Model Inference
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+ ```python
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+ from transformers import AutoTokenizer, AutoModelForCausalLM
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+ tokenizer = AutoTokenizer.from_pretrained("deepseek-ai/deepseek-coder-7b-instruct-v1.5", trust_remote_code=True)
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+ model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-7b-instruct-v1.5", trust_remote_code=True).cuda()
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+ messages=[
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+ { 'role': 'user', 'content': "write a quick sort algorithm in python."}
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+ ]
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+ inputs = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device)
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+
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+ outputs = model.generate(inputs, max_new_tokens=512, do_sample=False, top_k=50, top_p=0.95, num_return_sequences=1, eos_token_id=tokenizer.eos_token_id)
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+ print(tokenizer.decode(outputs[0][len(inputs[0]):], skip_special_tokens=True))
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+ ```
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+
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+ ### 3. License
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+ This code repository is licensed under the MIT License. The use of DeepSeek Coder models is subject to the Model License. DeepSeek Coder supports commercial use.
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+
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+ See the [LICENSE-MODEL](https://github.com/deepseek-ai/deepseek-coder/blob/main/LICENSE-MODEL) for more details.
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+
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+ ### 4. Contact
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+
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+ If you have any questions, please raise an issue or contact us at [service@deepseek.com](mailto:service@deepseek.com).
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+
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