add readme

README.md

@@ -0,0 +1,118 @@
+---
+license: mit
+library_name: transformers
+base_model:
+  - deepseek-ai/DeepSeek-V3.1-Base
+---
+# DeepSeek-V3.2-Exp
+
+<!-- markdownlint-disable first-line-h1 -->
+<!-- markdownlint-disable html -->
+<!-- markdownlint-disable no-duplicate-header -->
+
+<div align="center">
+  <img src="https://github.com/deepseek-ai/DeepSeek-V2/blob/main/figures/logo.svg?raw=true" width="60%" alt="DeepSeek-V3" />
+</div>
+<hr>
+<div align="center" style="line-height: 1;">
+  <a href="https://www.deepseek.com/" target="_blank" style="margin: 2px;">
+    <img alt="Homepage" src="https://github.com/deepseek-ai/DeepSeek-V2/blob/main/figures/badge.svg?raw=true" style="display: inline-block; vertical-align: middle;"/>
+  </a>
+  <a href="https://chat.deepseek.com/" target="_blank" style="margin: 2px;">
+    <img alt="Chat" src="https://img.shields.io/badge/🤖%20Chat-DeepSeek%20V3-536af5?color=536af5&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
+  </a>
+  <a href="https://huggingface.co/deepseek-ai" target="_blank" style="margin: 2px;">
+    <img alt="Hugging Face" src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-DeepSeek%20AI-ffc107?color=ffc107&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
+  </a>
+</div>
+<div align="center" style="line-height: 1;">
+  <a href="https://discord.gg/Tc7c45Zzu5" target="_blank" style="margin: 2px;">
+    <img alt="Discord" src="https://img.shields.io/badge/Discord-DeepSeek%20AI-7289da?logo=discord&logoColor=white&color=7289da" style="display: inline-block; vertical-align: middle;"/>
+  </a>
+  <a href="https://github.com/deepseek-ai/DeepSeek-V2/blob/main/figures/qr.jpeg?raw=true" target="_blank" style="margin: 2px;">
+    <img alt="Wechat" src="https://img.shields.io/badge/WeChat-DeepSeek%20AI-brightgreen?logo=wechat&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
+  </a>
+  <a href="https://twitter.com/deepseek_ai" target="_blank" style="margin: 2px;">
+    <img alt="Twitter Follow" src="https://img.shields.io/badge/Twitter-deepseek_ai-white?logo=x&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
+  </a>
+</div>
+<div align="center" style="line-height: 1;">
+  <a href="LICENSE" style="margin: 2px;">
+    <img alt="License" src="https://img.shields.io/badge/License-MIT-f5de53?&color=f5de53" style="display: inline-block; vertical-align: middle;"/>
+  </a>
+</div>
+
+## Introduction
+
+
+We are excited to announce the official release of DeepSeek-V3.2-Exp, an experimental version of our model. As an intermediate step toward our next-generation architecture, V3.2-Exp builds upon V3.1-Terminus by introducing DeepSeek Sparse Attention—a sparse attention mechanism designed to explore and validate optimizations for training and inference efficiency in long-context scenarios.
+
+This experimental release represents our ongoing research into more efficient transformer architectures, particularly focusing on improving computational efficiency when processing extended text sequences.
+
+<div align="center">
+ <img src="cost.jpg" >
+</div>
+
+- DeepSeek Sparse Attention (DSA) achieves fine-grained sparse attention for the first time, delivering substantial improvements in long-context training and inference efficiency while maintaining virtually identical model output quality.
+
+
+- To rigorously evaluate the impact of introducing sparse attention, we deliberately aligned the training configurations of DeepSeek-V3.2-Exp with V3.1-Terminus. Across public benchmarks in various domains, DeepSeek-V3.2-Exp demonstrates performance on par with V3.1-Terminus.
+
+
+| Benchmark | DeepSeek-V3.2 | DeepSeek-V3.1-Terminus |
+| :--- | :---: | :---: |
+| **Reasoning Mode w/o Tool Use** | | |
+| MMLU-Pro | 85.0 | 85.0 |
+| GPQA-Diamond | 79.9 | 80.7 |
+| Humanity's Last Exam | 19.8 | 21.7 |
+| LiveCodeBench | 74.1 | 74.9 |
+| AIME 2025 | 89.3 | 88.4 |
+| HMMT 2025 | 83.6 | 86.1 |
+| Codeforces | 2121 | 2046 |
+| Aider-Polyglot | 74.5 | 76.1 |
+| **Agentic Tool Use** | | |
+| BrowseComp | 40.1 | 38.5 |
+| BrowseComp-zh | 47.9 | 45.0 |
+| SimpleQA | 97.1 | 96.8 |
+| SWE Verified | 67.8 | 68.4 |
+| SWE-bench Multilingual | 57.9 | 57.8 |
+| Terminal-bench | 37.7 | 36.7 |
+
+
+
+## How to Run Locally
+
+We provide an updated inference demo code in the [inference](https://huggingface.co/deepseek-ai/DeepSeek-V3.2-Exp/tree/main/inference) folder to help the community quickly get started with our model and understand its architectural details.
+
+First convert huggingface model weights to the the format required by our inference demo. Set `MP` to match your available GPU count:
+```bash
+cd inference
+export EXPERTS=256
+python convert.py --hf-ckpt-path ${HF_CKPT_PATH} --save-path ${SAVE_PATH} --n-experts ${EXPERTS} --model-parallel ${MP}
+```
+
+Launch the interactive chat interface and start exploring DeepSeek's capabilities:
+```bash
+export CONFIG=config_671B_v3.2.json
+torchrun --nproc-per-node ${MP} generate.py --ckpt-path ${SAVE_PATH} --config ${CONFIG} --interactive
+```
+
+
+
+## License
+
+This repository and the model weights are licensed under the [MIT License](LICENSE).
+
+## Citation
+
+```
+@misc{deepseekai2024deepseekv32,
+      title={DeepSeek-V3.2-Exp: Boosting Long-Context Efficiency with DeepSeek Sparse Attention}, 
+      author={DeepSeek-AI},
+      year={2025},
+}
+```
+
+## Contact
+
+If you have any questions, please raise an issue or contact us at [[email protected]]([email protected]).

inference/README.md

@@ -1,12 +1,13 @@
 # DeepSeek V3.2
 
-First convert huggingface model weight files to the format of this project.
+First convert huggingface model weights to the the format required by our inference demo. Set `MP` to match your available GPU count:
 ```bash
+cd inference
 export EXPERTS=256
 python convert.py --hf-ckpt-path ${HF_CKPT_PATH} --save-path ${SAVE_PATH} --n-experts ${EXPERTS} --model-parallel ${MP}
 ```
 
-Then chat with DeepSeek model at will!
+Launch the interactive chat interface and start exploring DeepSeek's capabilities:
 ```bash
 export CONFIG=config_671B_v3.2.json
 torchrun --nproc-per-node ${MP} generate.py --ckpt-path ${SAVE_PATH} --config ${CONFIG} --interactive