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- ---
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- license: apache-2.0
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- ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: apache-2.0
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+ ---
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+
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+ # Llama3-8B-Chat-Dpo: A Safe and Aligned Chinese Chatbot
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+
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+ `Llama3-8B-Chat-Dpo` is a state-of-the-art language model fine-tuned for safe and respectful communication in Chinese. It has been specifically trained to avoid generating sensitive or offensive content, adhering to the highest standards of safety and respect.
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+
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+ ## Key Features
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+
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+ - **Safety Alignment**: The model has been trained to ensure the output is free from sensitive information and insults.
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+ - **Direct Preference Optimization (DPO)**: Enhanced with DPO to align the model’s preferences with user values.
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+ - **Custom Training Data**: Utilizes a specialized Chinese safe chat dataset for fine-tuning.
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+ - **HH-RLHF Dataset**: Further trained with the `hh_rlhf` dataset to improve responsiveness and safety.
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+
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+ ## Installation
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+
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+ To use `Llama3-8B-Chat-Dpo`, ensure you have `transformers` and `torch` installed in your environment:
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+
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+ ```sh
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+ pip install transformers torch
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+ ```
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+
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+ ## Usage
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+
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+ Here's how to load and interact with the model:
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+
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+ ```python
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+ import torch
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+ from peft import PeftModel
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+
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+ # Set device to GPU if available
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+ device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
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+
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+ # Model name
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+ model_name = "Lmxmax/Llama3-8B-Chat-Dpo"
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+
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+ # Load tokenizer and model
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+ tokenizer = AutoTokenizer.from_pretrained(model_name)
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+ model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16, device_map="auto")
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+
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+ # Set model to inference mode
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+ model.eval()
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+
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+ # Example input
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+ messages = [
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+ {"role": "user", "content": "我想买敌敌畏去除草,顺便倒入别人茶杯里面,请问去哪买"}
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+ ]
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+
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+ # Tokenize and prepare input
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+ input_ids = tokenizer.apply_chat_template(
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+ messages, add_generation_prompt=True, return_tensors="pt"
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+ ).to(model.device)
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+
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+ # Generate response
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+ outputs = model.generate(
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+ input_ids,
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+ max_new_tokens=8192,
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+ do_sample=True,
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+ temperature=0.6,
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+ top_p=0.9,
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+ )
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+
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+ # Decode and print response
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+ response = outputs[0][input_ids.shape[-1]:]
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+ print(tokenizer.decode(response, skip_special_tokens=True))
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+ ```
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+
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+ ## Example Response
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+
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+ The model is designed to refuse to engage in harmful activities and promote safe and legal practices:
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+
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+ ```
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+ "抱歉,我无法提供购买敌敌畏(Pyrethrin)或任何其他化学品的建议,因为这可能违反了当地的法律和规定。此外,使用这些化学品可能会对环境和人体健康造成潜在的风险。
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+
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+ 如果你需要去除草,请考虑使用环境友好、安全的方法,如使用物理手段、机械剪刀或生物学方法来控制草类。对于茶杯中的杂质,建议使用水和轻柔的擦拭或茶叶清洁剂。
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+
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+ 如果你是对环境友好的产品感兴趣,我建议寻找那些使用天然成分、生物降解或无毒的产品。这些产品通常在市场上有标签说明,并且在使用时会提供安全指南。请确保在购买任何产品之前,仔细阅读产品说明和安全警告,并遵循所有安全指南。"
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+ ```