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README.md

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+Quantization made by Richard Erkhov.
+
+[Github](https://github.com/RichardErkhov)
+
+[Discord](https://discord.gg/pvy7H8DZMG)
+
+[Request more models](https://github.com/RichardErkhov/quant_request)
+
+
+deepseek-coder-7b-base-v1.5 - GGUF
+- Model creator: https://huggingface.co/deepseek-ai/
+- Original model: https://huggingface.co/deepseek-ai/deepseek-coder-7b-base-v1.5/
+
+
+| Name | Quant method | Size |
+| ---- | ---- | ---- |
+| [deepseek-coder-7b-base-v1.5.Q2_K.gguf](https://huggingface.co/RichardErkhov/deepseek-ai_-_deepseek-coder-7b-base-v1.5-gguf/blob/main/deepseek-coder-7b-base-v1.5.Q2_K.gguf) | Q2_K | 2.53GB |
+| [deepseek-coder-7b-base-v1.5.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/deepseek-ai_-_deepseek-coder-7b-base-v1.5-gguf/blob/main/deepseek-coder-7b-base-v1.5.IQ3_XS.gguf) | IQ3_XS | 2.79GB |
+| [deepseek-coder-7b-base-v1.5.IQ3_S.gguf](https://huggingface.co/RichardErkhov/deepseek-ai_-_deepseek-coder-7b-base-v1.5-gguf/blob/main/deepseek-coder-7b-base-v1.5.IQ3_S.gguf) | IQ3_S | 2.92GB |
+| [deepseek-coder-7b-base-v1.5.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/deepseek-ai_-_deepseek-coder-7b-base-v1.5-gguf/blob/main/deepseek-coder-7b-base-v1.5.Q3_K_S.gguf) | Q3_K_S | 2.92GB |
+| [deepseek-coder-7b-base-v1.5.IQ3_M.gguf](https://huggingface.co/RichardErkhov/deepseek-ai_-_deepseek-coder-7b-base-v1.5-gguf/blob/main/deepseek-coder-7b-base-v1.5.IQ3_M.gguf) | IQ3_M | 3.06GB |
+| [deepseek-coder-7b-base-v1.5.Q3_K.gguf](https://huggingface.co/RichardErkhov/deepseek-ai_-_deepseek-coder-7b-base-v1.5-gguf/blob/main/deepseek-coder-7b-base-v1.5.Q3_K.gguf) | Q3_K | 3.22GB |
+| [deepseek-coder-7b-base-v1.5.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/deepseek-ai_-_deepseek-coder-7b-base-v1.5-gguf/blob/main/deepseek-coder-7b-base-v1.5.Q3_K_M.gguf) | Q3_K_M | 3.22GB |
+| [deepseek-coder-7b-base-v1.5.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/deepseek-ai_-_deepseek-coder-7b-base-v1.5-gguf/blob/main/deepseek-coder-7b-base-v1.5.Q3_K_L.gguf) | Q3_K_L | 3.49GB |
+| [deepseek-coder-7b-base-v1.5.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/deepseek-ai_-_deepseek-coder-7b-base-v1.5-gguf/blob/main/deepseek-coder-7b-base-v1.5.IQ4_XS.gguf) | IQ4_XS | 3.56GB |
+| [deepseek-coder-7b-base-v1.5.Q4_0.gguf](https://huggingface.co/RichardErkhov/deepseek-ai_-_deepseek-coder-7b-base-v1.5-gguf/blob/main/deepseek-coder-7b-base-v1.5.Q4_0.gguf) | Q4_0 | 3.73GB |
+| [deepseek-coder-7b-base-v1.5.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/deepseek-ai_-_deepseek-coder-7b-base-v1.5-gguf/blob/main/deepseek-coder-7b-base-v1.5.IQ4_NL.gguf) | IQ4_NL | 3.74GB |
+| [deepseek-coder-7b-base-v1.5.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/deepseek-ai_-_deepseek-coder-7b-base-v1.5-gguf/blob/main/deepseek-coder-7b-base-v1.5.Q4_K_S.gguf) | Q4_K_S | 3.75GB |
+| [deepseek-coder-7b-base-v1.5.Q4_K.gguf](https://huggingface.co/RichardErkhov/deepseek-ai_-_deepseek-coder-7b-base-v1.5-gguf/blob/main/deepseek-coder-7b-base-v1.5.Q4_K.gguf) | Q4_K | 3.93GB |
+| [deepseek-coder-7b-base-v1.5.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/deepseek-ai_-_deepseek-coder-7b-base-v1.5-gguf/blob/main/deepseek-coder-7b-base-v1.5.Q4_K_M.gguf) | Q4_K_M | 3.93GB |
+| [deepseek-coder-7b-base-v1.5.Q4_1.gguf](https://huggingface.co/RichardErkhov/deepseek-ai_-_deepseek-coder-7b-base-v1.5-gguf/blob/main/deepseek-coder-7b-base-v1.5.Q4_1.gguf) | Q4_1 | 4.1GB |
+| [deepseek-coder-7b-base-v1.5.Q5_0.gguf](https://huggingface.co/RichardErkhov/deepseek-ai_-_deepseek-coder-7b-base-v1.5-gguf/blob/main/deepseek-coder-7b-base-v1.5.Q5_0.gguf) | Q5_0 | 4.48GB |
+| [deepseek-coder-7b-base-v1.5.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/deepseek-ai_-_deepseek-coder-7b-base-v1.5-gguf/blob/main/deepseek-coder-7b-base-v1.5.Q5_K_S.gguf) | Q5_K_S | 4.48GB |
+| [deepseek-coder-7b-base-v1.5.Q5_K.gguf](https://huggingface.co/RichardErkhov/deepseek-ai_-_deepseek-coder-7b-base-v1.5-gguf/blob/main/deepseek-coder-7b-base-v1.5.Q5_K.gguf) | Q5_K | 4.59GB |
+| [deepseek-coder-7b-base-v1.5.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/deepseek-ai_-_deepseek-coder-7b-base-v1.5-gguf/blob/main/deepseek-coder-7b-base-v1.5.Q5_K_M.gguf) | Q5_K_M | 4.59GB |
+| [deepseek-coder-7b-base-v1.5.Q5_1.gguf](https://huggingface.co/RichardErkhov/deepseek-ai_-_deepseek-coder-7b-base-v1.5-gguf/blob/main/deepseek-coder-7b-base-v1.5.Q5_1.gguf) | Q5_1 | 4.86GB |
+| [deepseek-coder-7b-base-v1.5.Q6_K.gguf](https://huggingface.co/RichardErkhov/deepseek-ai_-_deepseek-coder-7b-base-v1.5-gguf/blob/main/deepseek-coder-7b-base-v1.5.Q6_K.gguf) | Q6_K | 5.28GB |
+| [deepseek-coder-7b-base-v1.5.Q8_0.gguf](https://huggingface.co/RichardErkhov/deepseek-ai_-_deepseek-coder-7b-base-v1.5-gguf/blob/main/deepseek-coder-7b-base-v1.5.Q8_0.gguf) | Q8_0 | 6.84GB |
+
+
+
+
+Original model description:
+---
+license: other
+license_name: deepseek-license
+license_link: LICENSE
+---
+
+<p align="center">
+<img width="1000px" alt="DeepSeek Coder" src="https://github.com/deepseek-ai/DeepSeek-Coder/blob/main/pictures/logo.png?raw=true">
+</p>
+<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>
+<hr>
+
+
+### 1. Introduction of Deepseek-Coder-7B-Base-v1.5
+
+Deepseek-Coder-7B-Base-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.
+
+- **Home Page:** [DeepSeek](https://deepseek.com/)
+- **Repository:** [deepseek-ai/deepseek-coder](https://github.com/deepseek-ai/deepseek-coder)
+- **Chat With DeepSeek Coder:** [DeepSeek-Coder](https://coder.deepseek.com/)
+
+
+### 2. Evaluation Results
+<img width="1000px" alt="DeepSeek Coder" src="https://cdn-uploads.huggingface.co/production/uploads/6538815d1bdb3c40db94fbfa/xOtCTW5xdoLCKY4FR6tri.png">
+
+
+
+### 3. How to Use
+Here give an example of how to use our model.
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+tokenizer = AutoTokenizer.from_pretrained("deepseek-ai/deepseek-coder-7b-base-v1.5", trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained("deepseek-ai/deepseek-coder-7b-base-v1.5", trust_remote_code=True).cuda()
+input_text = "#write a quick sort algorithm"
+inputs = tokenizer(input_text, return_tensors="pt").cuda()
+outputs = model.generate(**inputs, max_length=128)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+### 4. License
+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.
+
+See the [LICENSE-MODEL](https://github.com/deepseek-ai/deepseek-coder/blob/main/LICENSE-MODEL) for more details.
+
+### 5. Contact
+
+If you have any questions, please raise an issue or contact us at [service@deepseek.com](mailto:service@deepseek.com).
+
+