Update README.md

README.md

@@ -14,4 +14,36 @@ pipeline_tag: text-generation
 inference: false
 ---
 
-Trained by https://github.com/hiyouga/LLaMA-Efficient-Tuning
+A chinese instruction-tuned LoRA model of https://huggingface.co/baichuan-inc/Baichuan-13B-Base
+
+- Instruction-following datasets used: alpaca-zh, sharegpt
+- Training framework: https://github.com/hiyouga/LLaMA-Efficient-Tuning
+
+Usage:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
+
+tokenizer = AutoTokenizer.from_pretrained("hiyouga/baichuan-13b-sft", trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained("hiyouga/baichuan-13b-sft", trust_remote_code=True).cuda()
+streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
+
+query = "晚上睡不着怎么办"
+template = "A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions.\nHuman: {}\nAssistant: "
+
+inputs = tokenizer([template.format(query)], return_tensors="pt")
+inputs = inputs.to("cuda")
+generate_ids = model.generate(**inputs, max_new_tokens=256, streamer=streamer)
+```
+
+You could also alternatively launch a CLI demo by using the script in https://github.com/hiyouga/LLaMA-Efficient-Tuning
+
+```bash
+python src/cli_demo.py --model_name_or_path hiyouga/baichuan-13b-sft
+```
+
+---
+
+You can reproduce our results by visiting the following step-by-step (Chinese) guide:
+
+https://zhuanlan.zhihu.com/p/645010851