This is the LLaMAfied version of Baichuan2-7B-Chat model by Baichuan Inc.
This model is converted with https://github.com/hiyouga/LLaMA-Factory/blob/main/tests/llamafy_baichuan2.py
You may use this model for fine-tuning in downstream tasks, we recommend using our efficient fine-tuning toolkit. https://github.com/hiyouga/LLaMA-Factory
- Developed by: Baichuan Inc.
- Language(s) (NLP): Chinese/English
- License: Baichuan2 License
Usage:
from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
tokenizer = AutoTokenizer.from_pretrained("hiyouga/Baichuan2-7B-Chat-LLaMAfied", use_fast=False)
model = AutoModelForCausalLM.from_pretrained("hiyouga/Baichuan2-7B-Chat-LLaMAfied").cuda()
streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
query = "<reserved_106>晚上睡不着怎么办<reserved_107>"
inputs = tokenizer([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 LLaMA-Factory
python src/cli_demo.py --template baichuan2 --model_name_or_path hiyouga/Baichuan2-7B-Chat-LLaMAfied
Open LLM Leaderboard Evaluation Results
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 47.92 |
| ARC (25-shot) | 52.47 |
| HellaSwag (10-shot) | 74.04 |
| MMLU (5-shot) | 53.88 |
| TruthfulQA (0-shot) | 48.04 |
| Winogrande (5-shot) | 69.14 |
| GSM8K (5-shot) | 10.92 |
| DROP (3-shot) | 26.94 |