Instructions to use EuropeanTurtle/DialoGPT-small-mrcobb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EuropeanTurtle/DialoGPT-small-mrcobb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="EuropeanTurtle/DialoGPT-small-mrcobb") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("EuropeanTurtle/DialoGPT-small-mrcobb") model = AutoModelForCausalLM.from_pretrained("EuropeanTurtle/DialoGPT-small-mrcobb") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use EuropeanTurtle/DialoGPT-small-mrcobb with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "EuropeanTurtle/DialoGPT-small-mrcobb" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "EuropeanTurtle/DialoGPT-small-mrcobb", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/EuropeanTurtle/DialoGPT-small-mrcobb
- SGLang
How to use EuropeanTurtle/DialoGPT-small-mrcobb 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 "EuropeanTurtle/DialoGPT-small-mrcobb" \ --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": "EuropeanTurtle/DialoGPT-small-mrcobb", "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 "EuropeanTurtle/DialoGPT-small-mrcobb" \ --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": "EuropeanTurtle/DialoGPT-small-mrcobb", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use EuropeanTurtle/DialoGPT-small-mrcobb with Docker Model Runner:
docker model run hf.co/EuropeanTurtle/DialoGPT-small-mrcobb
- Xet hash:
- 119ce67d62c8b99b05bd375982d2d4a7ebd86551b74f80dd86d8aa2c8834ac16
- Size of remote file:
- 510 MB
- SHA256:
- 50574b30a4a3e3aa1c264d145014b41f648776682e21bff82d35a4c87055b09d
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