Instructions to use FreedomIntelligence/HuatuoGPT2-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use FreedomIntelligence/HuatuoGPT2-7B with Transformers:

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

pipe = pipeline("text-generation", model="FreedomIntelligence/HuatuoGPT2-7B", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("FreedomIntelligence/HuatuoGPT2-7B", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use FreedomIntelligence/HuatuoGPT2-7B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "FreedomIntelligence/HuatuoGPT2-7B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "FreedomIntelligence/HuatuoGPT2-7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/FreedomIntelligence/HuatuoGPT2-7B

SGLang

How to use FreedomIntelligence/HuatuoGPT2-7B 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 "FreedomIntelligence/HuatuoGPT2-7B" \
    --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": "FreedomIntelligence/HuatuoGPT2-7B",
		"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 "FreedomIntelligence/HuatuoGPT2-7B" \
        --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": "FreedomIntelligence/HuatuoGPT2-7B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use FreedomIntelligence/HuatuoGPT2-7B with Docker Model Runner:
```
docker model run hf.co/FreedomIntelligence/HuatuoGPT2-7B
```

jymcc commited on Nov 23, 2023

Commit

7d75020

1 Parent(s): c66d1e3

Update README.md

Browse files

Files changed (1) hide show

README.md +3 -3

README.md CHANGED Viewed

@@ -24,9 +24,9 @@ tasks:
 import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer
 from transformers.generation.utils import GenerationConfig
-tokenizer = AutoTokenizer.from_pretrained("FreedomIntelligence/HuatuoGPT-2-7b", use_fast=True, trust_remote_code=True)
-model = AutoModelForCausalLM.from_pretrained("FreedomIntelligence/HuatuoGPT-2-7b", device_map="auto", torch_dtype=torch.bfloat16, trust_remote_code=True)
-model.generation_config = GenerationConfig.from_pretrained("FreedomIntelligence/HuatuoGPT-2-7b")
 messages = []
 messages.append({"role": "user", "content": "肚子疼怎么办？"})
 response = model.HuatuoChat(tokenizer, messages)

 import torch
 from transformers import AutoModelForCausalLM, AutoTokenizer
 from transformers.generation.utils import GenerationConfig
+tokenizer = AutoTokenizer.from_pretrained("FreedomIntelligence/HuatuoGPT2-7B", use_fast=True, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained("FreedomIntelligence/HuatuoGPT2-7B", device_map="auto", torch_dtype=torch.bfloat16, trust_remote_code=True)
+model.generation_config = GenerationConfig.from_pretrained("FreedomIntelligence/HuatuoGPT2-7B")
 messages = []
 messages.append({"role": "user", "content": "肚子疼怎么办？"})
 response = model.HuatuoChat(tokenizer, messages)