Update README.md

README.md

@@ -1,3 +1,85 @@
----
-license: apache-2.0
----
+---
+license: mit
+language:
+- zh
+- en
+base_model:
+- deepseek-ai/deepseek-llm-7b-chat
+---
+# Deep **<u>Seek</u>-<u>Fake</u>-<u>News</u>** LLM
+<!-- markdownlint-disable first-line-h1 -->
+<!-- markdownlint-disable html -->
+<!-- markdownlint-disable no-duplicate-header -->
+
+<div align="center">
+  <img src="figures/logo_v1.0.png" width="60%" alt="DeepSeekFakeNews-LLM" />
+</div>
+
+<p align="center">
+  <a href="https://github.com/TAN-OpenLab"><b>Project Link</b>👁️</a>
+  <a href="http://faculty.neu.edu.cn/tanzhenhua/zh_CN/index/100352/list/index.htm"><b>Lab Link</b>👁️</a>
+</p>
+
+
+### 1. Introduction of Deep **<u>Seek</u>-<u>Fake</u>-<u>News</u>** LLM
+
+  
+### 2. Model Summary
+`deepseekfakenews-llm-7b-chat` is a 7B parameter model initialized from `deepseek-llm-7b-chat` and fine-tuned on extra fake news instruction data.
+
+- **Home Page:** [DeepSeekFakeNews](https://deepseek.com/)
+- **Repository:** [zt-ai/DeepSeekFakeNews-LLM-7B-Chat](https://github.com/TAN-OpenLab)
+- **Demo of Chatting With DeepSeekFakeNews-LLM: to comment soon!
+
+
+### 3. How to Use
+Here are some examples of how to use our model.
+
+```python
+import torch
+from peft import PeftModel
+from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig
+
+model_name = "zt-ai/DeepSeekFakeNews-llm-7b-chat"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+model.generation_config = GenerationConfig.from_pretrained(model_name)
+model.generation_config.pad_token_id = model.generation_config.eos_token_id
+lora_model = PeftModel.from_pretrained(base_model, model_name)
+
+
+messages = [
+    {
+"role": "user",
+"content":
+"""假新闻的表现可以总结为以下几个方面：1. 逻辑和事实矛盾。2.断章取义和误导性信息。3.夸张标题和吸引眼球的内容。4.情绪化和极端语言。5.偏见和单一立场。请从这几个方面分析新闻的真实性（真新闻或假新闻）：
+发布时间：
+新闻标题：
+新闻内容：
+"""}
+]
+input_tensor = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt")
+outputs = model.generate(input_tensor.to(model.device), max_new_tokens=100)
+
+result = tokenizer.decode(outputs[0][input_tensor.shape[1]:], skip_special_tokens=True)
+print(result)
+```
+
+Avoiding the use of the provided function `apply_chat_template`, you can also interact with our model following the sample template. Note that `messages` should be replaced by your input.
+
+```
+User: {messages[0]['content']}
+
+Assistant: 
+```
+
+**Note:** By default (`add_special_tokens=True`), our tokenizer automatically adds a `bos_token` (`<｜begin▁of▁sentence｜>`) before the input text. Additionally, since the system prompt is not compatible with this version of our models, we DO NOT RECOMMEND including the system prompt in your input.
+
+### 4. License
+This code repository is licensed under the MIT License. The use of DeepSeekFakeNews-LLM models is subject to the Model License. DeepSeekFakeNews-LLM supports commercial use.
+
+<!-- See the [LICENSE-MODEL](https://github.com/deepseek-ai/deepseek-LLM/blob/main/LICENSE-MODEL) for more details. -->
+
+### 5. Contact
+
+If you have any questions, please raise an issue or contact us at [[email protected]](mailto:[email protected]).