Instructions to use Guard-SK/DialoGPT-medium-ricksanchez with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Guard-SK/DialoGPT-medium-ricksanchez with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Guard-SK/DialoGPT-medium-ricksanchez") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Guard-SK/DialoGPT-medium-ricksanchez") model = AutoModelForCausalLM.from_pretrained("Guard-SK/DialoGPT-medium-ricksanchez") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Guard-SK/DialoGPT-medium-ricksanchez with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Guard-SK/DialoGPT-medium-ricksanchez" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Guard-SK/DialoGPT-medium-ricksanchez", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Guard-SK/DialoGPT-medium-ricksanchez
- SGLang
How to use Guard-SK/DialoGPT-medium-ricksanchez 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 "Guard-SK/DialoGPT-medium-ricksanchez" \ --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": "Guard-SK/DialoGPT-medium-ricksanchez", "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 "Guard-SK/DialoGPT-medium-ricksanchez" \ --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": "Guard-SK/DialoGPT-medium-ricksanchez", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Guard-SK/DialoGPT-medium-ricksanchez with Docker Model Runner:
docker model run hf.co/Guard-SK/DialoGPT-medium-ricksanchez
- Xet hash:
- 3742077e24706c9deeed25bbf4cdcab974e33e96209d4f1c01ee13ebc22f62c1
- Size of remote file:
- 510 MB
- SHA256:
- 1cf63c346272b430bb61faccd7b79eb38be09b275c7dd49a0f1de66a697765da
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