Instructions to use fireballoon/baichuan-vicuna-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use fireballoon/baichuan-vicuna-7b with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="fireballoon/baichuan-vicuna-7b")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("fireballoon/baichuan-vicuna-7b")
model = AutoModelForCausalLM.from_pretrained("fireballoon/baichuan-vicuna-7b")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use fireballoon/baichuan-vicuna-7b with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "fireballoon/baichuan-vicuna-7b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "fireballoon/baichuan-vicuna-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/fireballoon/baichuan-vicuna-7b

SGLang

How to use fireballoon/baichuan-vicuna-7b with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "fireballoon/baichuan-vicuna-7b" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "fireballoon/baichuan-vicuna-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "fireballoon/baichuan-vicuna-7b" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "fireballoon/baichuan-vicuna-7b",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use fireballoon/baichuan-vicuna-7b with Docker Model Runner:
```
docker model run hf.co/fireballoon/baichuan-vicuna-7b
```

关于模型中文语言表现

by reedhs - opened Jun 21, 2023

Discussion

reedhs

Jun 21, 2023

感谢作者的工作！
想请教一下，目前我看到您的instruction fintuning 语料主要都是英文语料，但是中文输出效果尚可，因此有一个疑问：之前使用 LLama vicuna-7b 时常会出现中文问、模型英文回答的情况，感觉原因是英文的finetune过多导致（当然和llama本身也有关系），不知道这种现象在本模型使用中是否常出现？或者说您采用了什么办法来减少或避免此问题？谢谢！

fireballoon

Owner Jun 29, 2023

本模型会出现问中文回答英文的问题，在一些特点问题上比较频繁。
ShareGPT中有一定比例的中文数据，baichuan-7b也在更多中文语料上训练，可能有助于缓解这个问题。
避免此问题可以在更多中文问中文答的数据上微调。

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment