Update README.md

README.md

@@ -1,3 +1,41 @@
 ---
 license: llama2
+datasets:
+- tatsu-lab/alpaca
+- OpenAssistant/oasst1
+pipeline_tag: text-generation
 ---
+
+A bilingual instruction-tuned LoRA model of https://huggingface.co/meta-llama/Llama-2-13b-hf
+
+- Instruction-following datasets used: alpaca, alpaca-zh, openassistant
+- Training framework: https://github.com/hiyouga/LLaMA-Efficient-Tuning
+
+Usage:
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
+
+tokenizer = AutoTokenizer.from_pretrained("hiyouga/Llama-2-Chinese-13b-chat")
+model = AutoModelForCausalLM.from_pretrained("hiyouga/Llama-2-Chinese-13b-chat").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.\n"
+    "Human: {}\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/Llama-2-Chinese-13b-chat
+```
+
+---