Instructions to use rajpurkar/distilgpt2-squad with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rajpurkar/distilgpt2-squad with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="rajpurkar/distilgpt2-squad")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("rajpurkar/distilgpt2-squad") model = AutoModelForCausalLM.from_pretrained("rajpurkar/distilgpt2-squad", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use rajpurkar/distilgpt2-squad with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "rajpurkar/distilgpt2-squad" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rajpurkar/distilgpt2-squad", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/rajpurkar/distilgpt2-squad
- SGLang
How to use rajpurkar/distilgpt2-squad 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 "rajpurkar/distilgpt2-squad" \ --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": "rajpurkar/distilgpt2-squad", "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 "rajpurkar/distilgpt2-squad" \ --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": "rajpurkar/distilgpt2-squad", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use rajpurkar/distilgpt2-squad with Docker Model Runner:
docker model run hf.co/rajpurkar/distilgpt2-squad
add model
Browse files- .gitignore +1 -0
- merges.txt +0 -0
- pytorch_model.bin +1 -1
- special_tokens_map.json +5 -0
- tokenizer.json +0 -0
- tokenizer_config.json +10 -0
- vocab.json +0 -0
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tokenizer.json
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tokenizer_config.json
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"eos_token": "<|endoftext|>",
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"model_max_length": 1024,
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"name_or_path": "distilgpt2",
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"special_tokens_map_file": null,
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"tokenizer_class": "GPT2Tokenizer",
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