---
license: apache-2.0
datasets:
- liyucheng/zhihu_rlhf_3k
language:
- zh
base_model:
- lucky2me/Dorami-Instruct
---

# Dorami-Chat

    Dorami-Chat is a Direct Preference Optimization(DPO) model based on the Supervised Fine-tuning(SFT) model lucky2me/Dorami-Instruct

## Model description

### Training data

-    [liyucheng/zhihu_rlhf_3k](https://huggingface.co/datasets/liyucheng/zhihu_rlhf_3k)

### Training code

-    [dorami](https://github.com/6zeus/dorami.git)

## How to use

### 1. Download model from Hugging Face Hub to local

``` 
git lfs install
git clone https://huggingface.co/lucky2me/Dorami-Chat
```

### 2. Use the model downloaded above 
```python
from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig
model_path = "The path of the model downloaded above"
tokenizer = AutoTokenizer.from_pretrained(model_path)
model = AutoModelForCausalLM.from_pretrained(model_path)
prompt="fill in any prompt you like."
inputs = tokenizer(prompt, return_tensors="pt")
generation_config = GenerationConfig(max_new_tokens=64, do_sample=True, top_k=2, eos_token_id=model.config.eos_token_id)
outputs = model.generate(**inputs, generation_config=generation_config)
decoded_text = tokenizer.batch_decode(outputs, skip_special_tokens=True)
print(decoded_text)
```