AlpaGasus: Training A Better Alpaca with Fewer Data
Paper • 2307.08701 • Published • 24
How to use gpt4life/alpagasus-7b with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="gpt4life/alpagasus-7b") # Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("gpt4life/alpagasus-7b")
model = AutoModelForCausalLM.from_pretrained("gpt4life/alpagasus-7b", device_map="auto")How to use gpt4life/alpagasus-7b with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "gpt4life/alpagasus-7b"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "gpt4life/alpagasus-7b",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'docker model run hf.co/gpt4life/alpagasus-7b
How to use gpt4life/alpagasus-7b with SGLang:
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
--model-path "gpt4life/alpagasus-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": "gpt4life/alpagasus-7b",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'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 "gpt4life/alpagasus-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": "gpt4life/alpagasus-7b",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'How to use gpt4life/alpagasus-7b with Docker Model Runner:
docker model run hf.co/gpt4life/alpagasus-7b
This is an unofficial implementation of AlpaGasus-7B, which is a chat assistant trained by fine-tuning LLaMA on a Claud-filtered Alpaca dataset with around 5K triplets.
Please see the original LLaMA license before using this model.
AlpaGasus-7B is fine-tuned from LLaMA-7B with supervised instruction fine-tuning on the filtered Alpaca dataset.