Instructions to use TrebleJeff/DialoGPT-small-Michael with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TrebleJeff/DialoGPT-small-Michael with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="TrebleJeff/DialoGPT-small-Michael") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("TrebleJeff/DialoGPT-small-Michael") model = AutoModelForCausalLM.from_pretrained("TrebleJeff/DialoGPT-small-Michael") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use TrebleJeff/DialoGPT-small-Michael with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TrebleJeff/DialoGPT-small-Michael" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TrebleJeff/DialoGPT-small-Michael", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/TrebleJeff/DialoGPT-small-Michael
- SGLang
How to use TrebleJeff/DialoGPT-small-Michael 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 "TrebleJeff/DialoGPT-small-Michael" \ --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": "TrebleJeff/DialoGPT-small-Michael", "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 "TrebleJeff/DialoGPT-small-Michael" \ --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": "TrebleJeff/DialoGPT-small-Michael", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use TrebleJeff/DialoGPT-small-Michael with Docker Model Runner:
docker model run hf.co/TrebleJeff/DialoGPT-small-Michael
- Xet hash:
- d3f419252751b46019a0c462c19a2186e9e3de1c2a0828e00efd7583711dae4d
- Size of remote file:
- 996 MB
- SHA256:
- 894476ff74b2b89903f1251847ca984a585f52435d6c32b8189054e150d62aaa
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