Improve language tag

README.md

@@ -1,80 +1,91 @@
----
-license: apache-2.0
-datasets:
-- FreedomIntelligence/medical-o1-reasoning-SFT
-- FreedomIntelligence/medical-o1-verifiable-problem
-language:
-- en
-- zh
-base_model:
-- Qwen/Qwen2.5-7B-Instruct
-pipeline_tag: text-generation
-tags:
-- medical
----
-
-<div align="center">
-<h1>
-  HuatuoGPT-o1-7B
-</h1>
-</div>
-
-<div align="center">
-<a href="https://github.com/FreedomIntelligence/HuatuoGPT-o1" target="_blank">GitHub</a> | <a href="https://arxiv.org/pdf/2412.18925" target="_blank">Paper</a>
-</div>
-
-# <span>Introduction</span>
-**HuatuoGPT-o1** is a medical LLM designed for advanced medical reasoning.  It generates a complex thought process, reflecting and refining its reasoning, before providing a final response. 
-
-For more information, visit our GitHub repository: 
-[https://github.com/FreedomIntelligence/HuatuoGPT-o1](https://github.com/FreedomIntelligence/HuatuoGPT-o1).
-
-# <span>Model Info</span>
-|                      | Backbone     | Supported Languages | Link                                                                  |
-| -------------------- | ------------ | ----- | --------------------------------------------------------------------- |
-| **HuatuoGPT-o1-8B**  | LLaMA-3.1-8B  | English    | [HF Link](https://huggingface.co/FreedomIntelligence/HuatuoGPT-o1-8B) |
-| **HuatuoGPT-o1-70B** | LLaMA-3.1-70B | English    | [HF Link](https://huggingface.co/FreedomIntelligence/HuatuoGPT-o1-70B) |
-| **HuatuoGPT-o1-7B**  | Qwen2.5-7B   | English & Chinese | [HF Link](https://huggingface.co/FreedomIntelligence/HuatuoGPT-o1-7B) |
-| **HuatuoGPT-o1-72B** | Qwen2.5-72B  | English & Chinese | [HF Link](https://huggingface.co/FreedomIntelligence/HuatuoGPT-o1-72B) |
-
-
-
-# <span>Usage</span>
-You can use HuatuoGPT-o1-7B in the same way as `Qwen2.5-7B-Instruct`. You can deploy it with tools like [vllm](https://github.com/vllm-project/vllm) or [Sglang](https://github.com/sgl-project/sglang),  or perform direct inference:
-```python
-from transformers import AutoModelForCausalLM, AutoTokenizer
-
-model = AutoModelForCausalLM.from_pretrained("FreedomIntelligence/HuatuoGPT-o1-7B",torch_dtype="auto",device_map="auto")
-tokenizer = AutoTokenizer.from_pretrained("FreedomIntelligence/HuatuoGPT-o1-7B")
-
-input_text = "How to stop a cough?"
-messages = [{"role": "user", "content": input_text}]
-
-inputs = tokenizer(tokenizer.apply_chat_template(messages, tokenize=False,add_generation_prompt=True
-), return_tensors="pt").to(model.device)
-outputs = model.generate(**inputs, max_new_tokens=2048)
-print(tokenizer.decode(outputs[0], skip_special_tokens=True))
-```
-
-HuatuoGPT-o1 adopts a *thinks-before-it-answers* approach, with outputs formatted as:
-
-```
-## Thinking
-[Reasoning process]
-
-## Final Response
-[Output]
-```
-
-# <span>📖 Citation</span>
-```
-@misc{chen2024huatuogpto1medicalcomplexreasoning,
-      title={HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs}, 
-      author={Junying Chen and Zhenyang Cai and Ke Ji and Xidong Wang and Wanlong Liu and Rongsheng Wang and Jianye Hou and Benyou Wang},
-      year={2024},
-      eprint={2412.18925},
-      archivePrefix={arXiv},
-      primaryClass={cs.CL},
-      url={https://arxiv.org/abs/2412.18925}, 
-}
+---
+license: apache-2.0
+datasets:
+- FreedomIntelligence/medical-o1-reasoning-SFT
+- FreedomIntelligence/medical-o1-verifiable-problem
+language:
+- zho
+- eng
+- fra
+- spa
+- por
+- deu
+- ita
+- rus
+- jpn
+- kor
+- vie
+- tha
+- ara
+base_model:
+- Qwen/Qwen2.5-7B-Instruct
+pipeline_tag: text-generation
+tags:
+- medical
+---
+
+<div align="center">
+<h1>
+  HuatuoGPT-o1-7B
+</h1>
+</div>
+
+<div align="center">
+<a href="https://github.com/FreedomIntelligence/HuatuoGPT-o1" target="_blank">GitHub</a> | <a href="https://arxiv.org/pdf/2412.18925" target="_blank">Paper</a>
+</div>
+
+# <span>Introduction</span>
+**HuatuoGPT-o1** is a medical LLM designed for advanced medical reasoning.  It generates a complex thought process, reflecting and refining its reasoning, before providing a final response. 
+
+For more information, visit our GitHub repository: 
+[https://github.com/FreedomIntelligence/HuatuoGPT-o1](https://github.com/FreedomIntelligence/HuatuoGPT-o1).
+
+# <span>Model Info</span>
+|                      | Backbone     | Supported Languages | Link                                                                  |
+| -------------------- | ------------ | ----- | --------------------------------------------------------------------- |
+| **HuatuoGPT-o1-8B**  | LLaMA-3.1-8B  | English    | [HF Link](https://huggingface.co/FreedomIntelligence/HuatuoGPT-o1-8B) |
+| **HuatuoGPT-o1-70B** | LLaMA-3.1-70B | English    | [HF Link](https://huggingface.co/FreedomIntelligence/HuatuoGPT-o1-70B) |
+| **HuatuoGPT-o1-7B**  | Qwen2.5-7B   | English & Chinese | [HF Link](https://huggingface.co/FreedomIntelligence/HuatuoGPT-o1-7B) |
+| **HuatuoGPT-o1-72B** | Qwen2.5-72B  | English & Chinese | [HF Link](https://huggingface.co/FreedomIntelligence/HuatuoGPT-o1-72B) |
+
+
+
+# <span>Usage</span>
+You can use HuatuoGPT-o1-7B in the same way as `Qwen2.5-7B-Instruct`. You can deploy it with tools like [vllm](https://github.com/vllm-project/vllm) or [Sglang](https://github.com/sgl-project/sglang),  or perform direct inference:
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("FreedomIntelligence/HuatuoGPT-o1-7B",torch_dtype="auto",device_map="auto")
+tokenizer = AutoTokenizer.from_pretrained("FreedomIntelligence/HuatuoGPT-o1-7B")
+
+input_text = "How to stop a cough?"
+messages = [{"role": "user", "content": input_text}]
+
+inputs = tokenizer(tokenizer.apply_chat_template(messages, tokenize=False,add_generation_prompt=True
+), return_tensors="pt").to(model.device)
+outputs = model.generate(**inputs, max_new_tokens=2048)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+HuatuoGPT-o1 adopts a *thinks-before-it-answers* approach, with outputs formatted as:
+
+```
+## Thinking
+[Reasoning process]
+
+## Final Response
+[Output]
+```
+
+# <span>📖 Citation</span>
+```
+@misc{chen2024huatuogpto1medicalcomplexreasoning,
+      title={HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs}, 
+      author={Junying Chen and Zhenyang Cai and Ke Ji and Xidong Wang and Wanlong Liu and Rongsheng Wang and Jianye Hou and Benyou Wang},
+      year={2024},
+      eprint={2412.18925},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2412.18925}, 
+}
 ```