Instructions to use Wise/DialogGPT-small-JC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Wise/DialogGPT-small-JC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Wise/DialogGPT-small-JC") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Wise/DialogGPT-small-JC") model = AutoModelForCausalLM.from_pretrained("Wise/DialogGPT-small-JC") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Wise/DialogGPT-small-JC with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Wise/DialogGPT-small-JC" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Wise/DialogGPT-small-JC", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Wise/DialogGPT-small-JC
- SGLang
How to use Wise/DialogGPT-small-JC 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 "Wise/DialogGPT-small-JC" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Wise/DialogGPT-small-JC", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "Wise/DialogGPT-small-JC" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Wise/DialogGPT-small-JC", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Wise/DialogGPT-small-JC with Docker Model Runner:
docker model run hf.co/Wise/DialogGPT-small-JC
- Xet hash:
- 373b3406b23285328da4538e6374b4ff11f02e943ca3d99cc829659061bf8f86
- Size of remote file:
- 996 MB
- SHA256:
- b2587cb7d2f4ec8972fffc252c4fe514b086193264f07c0cfb1222a0ce0ec22d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.