Create README.md

README.md

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+---
+license: apache-2.0
+datasets:
+- BelleGroup/train_0.5M_CN
+language:
+- en
+- zh
+tags:
+- text-generation-inference
+widget:
+- text: |-
+    <|im_start|>user
+    请以『春天的北京』为题写一首诗歌
+    <|im_end|>
+    <|im_start|>assistant
+  example_title: generation zh
+---
+# Baichuan 7B ChatML
+
+## 介绍 Introduction
+
+`baichuan-7B-chatml` 是支持多轮对话兼容于 ChatML 的模型。
+模型基于 [baichuan-7B](https://huggingface.co/baichuan-inc/baichuan-7B) 微调而成。
+`baichuan-7B-chatml` 模型支持商用。但按照baichuan-7B的要求，如果将baichuan-7B衍生品用作商业用途，需要联系[baichuan-7B 的许可方](https://github.com/baichuan-inc/baichuan-7B#%E5%8D%8F%E8%AE%AE)。
+
+__需要注意：在面对事实性知识任务时，模型可能会生成不正确的信息或者产生不稳定的输出（有时可以返回正确答案，有时不能）。__
+
+`baichuan-7B-chatml` is a model that supports multi-turn dialog and is compatible with ChatML.
+The model is fine-tuned based on [baichuan-7B](https://huggingface.co/baichuan-inc/baichuan-7B).
+`baichuan-7B-chatml` model supports commercial use. However, according to the requirements of baichuan-7B, if baichuan-7B derivatives are used for commercial purposes, you need to contact [baichuan-7B](https://github.com/baichuan-inc/baichuan-7B#%E5%8D%8F%E8%AE%AE)。
+
+__Note: When dealing with factual knowledge tasks, it may generate incorrect information or unstable output (sometimes it can return the correct answer, sometimes not).__
+
+## 代码示例 Examples
+
+模型在百川的基础上提供了对轮对话的函数供调用。
+
+The model provides a function for multi-turn dialogs.
+
+```ipython
+>>> from transformers import AutoTokenizer, AutoModelForCausalLM
+>>> tokenizer = AutoTokenizer.from_pretrained("tibok/baichuan-7B-chatml", trust_remote_code=True)
+>>> model = AutoModelForCausalLM.from_pretrained("tibok/baichuan-7B-chatml", device_map="auto", trust_remote_code=True)
+>>> response, history = model.chat(tokenizer, "请以『春天的北京』为题写一首诗歌", history=[])
+春天的北京，
+花开万丈，
+春意盎然，
+清风送暖。
+<|im_end|>
+>>> response, history = model.chat(tokenizer, "能不能再写一首关于香山的？", history=history)
+>>> print(response)
+香山之巅，
+芳草连天。
+清泉潺潺，
+山峦绵绵。
+<|im_end|>
+```
+
+## 更多细节 Details
+
+- Dataset： [BelleGroup/train_0.5M_CN](https://huggingface.co/datasets/BelleGroup/train_0.5M_CN) 
+- steps: 13800
+- batch_size: 8
+- seq_len： 2048