HuatuoGPT-2
Collection
HuatuoGPT2, One-stage Training for Medical Adaption of LLMs • 6 items • Updated • 2
How to use FreedomIntelligence/HuatuoGPT2-34B with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="FreedomIntelligence/HuatuoGPT2-34B", trust_remote_code=True) # Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("FreedomIntelligence/HuatuoGPT2-34B", trust_remote_code=True, dtype="auto")How to use FreedomIntelligence/HuatuoGPT2-34B with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "FreedomIntelligence/HuatuoGPT2-34B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "FreedomIntelligence/HuatuoGPT2-34B",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'docker model run hf.co/FreedomIntelligence/HuatuoGPT2-34B
How to use FreedomIntelligence/HuatuoGPT2-34B with SGLang:
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
--model-path "FreedomIntelligence/HuatuoGPT2-34B" \
--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": "FreedomIntelligence/HuatuoGPT2-34B",
"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 "FreedomIntelligence/HuatuoGPT2-34B" \
--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": "FreedomIntelligence/HuatuoGPT2-34B",
"prompt": "Once upon a time,",
"max_tokens": 512,
"temperature": 0.5
}'How to use FreedomIntelligence/HuatuoGPT2-34B with Docker Model Runner:
docker model run hf.co/FreedomIntelligence/HuatuoGPT2-34B
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("FreedomIntelligence/HuatuoGPT2-34B", trust_remote_code=True, dtype="auto")import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
from transformers.generation.utils import GenerationConfig
tokenizer = AutoTokenizer.from_pretrained("FreedomIntelligence/HuatuoGPT2-34B", use_fast=True, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("FreedomIntelligence/HuatuoGPT2-34B", device_map="auto", torch_dtype="auto", trust_remote_code=True)
model.generation_config = GenerationConfig.from_pretrained("FreedomIntelligence/HuatuoGPT2-34B")
messages = []
messages.append({"role": "user", "content": "肚子疼怎么办?"})
response = model.HuatuoChat(tokenizer, messages)
print(response)
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="FreedomIntelligence/HuatuoGPT2-34B", trust_remote_code=True)