Instructions to use CallumRai/HansardGPT2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CallumRai/HansardGPT2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="CallumRai/HansardGPT2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("CallumRai/HansardGPT2") model = AutoModelForCausalLM.from_pretrained("CallumRai/HansardGPT2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use CallumRai/HansardGPT2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "CallumRai/HansardGPT2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "CallumRai/HansardGPT2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/CallumRai/HansardGPT2
- SGLang
How to use CallumRai/HansardGPT2 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 "CallumRai/HansardGPT2" \ --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": "CallumRai/HansardGPT2", "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 "CallumRai/HansardGPT2" \ --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": "CallumRai/HansardGPT2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use CallumRai/HansardGPT2 with Docker Model Runner:
docker model run hf.co/CallumRai/HansardGPT2
Download pytorch_model.bin from CallumRai/HansardGPT2: direct link, hf CLI and curl.
- Browser
- Download file 510 MB
-
https://huggingface.co/CallumRai/HansardGPT2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://CallumRai/HansardGPT2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/CallumRai/HansardGPT2/resolve/main/pytorch_model.bin
510 MB
- Xet hash:
- 17b6b2bdad5a64ce7e2e38801b089184d27a27e39ba163c58a3d8e50003bc3f4
- Size of remote file:
- 510 MB
- SHA256:
- 75bfd4a9906714c7e32917d4640e61309a14cf08c1d442ca1ffeeac5c9b6e2ab
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