Instructions to use arithmetic-circuit-overloading/gpt2-64D-1L-2H with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arithmetic-circuit-overloading/gpt2-64D-1L-2H with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="arithmetic-circuit-overloading/gpt2-64D-1L-2H")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("arithmetic-circuit-overloading/gpt2-64D-1L-2H") model = AutoModelForCausalLM.from_pretrained("arithmetic-circuit-overloading/gpt2-64D-1L-2H") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use arithmetic-circuit-overloading/gpt2-64D-1L-2H with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "arithmetic-circuit-overloading/gpt2-64D-1L-2H" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "arithmetic-circuit-overloading/gpt2-64D-1L-2H", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/arithmetic-circuit-overloading/gpt2-64D-1L-2H
- SGLang
How to use arithmetic-circuit-overloading/gpt2-64D-1L-2H 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 "arithmetic-circuit-overloading/gpt2-64D-1L-2H" \ --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": "arithmetic-circuit-overloading/gpt2-64D-1L-2H", "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 "arithmetic-circuit-overloading/gpt2-64D-1L-2H" \ --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": "arithmetic-circuit-overloading/gpt2-64D-1L-2H", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use arithmetic-circuit-overloading/gpt2-64D-1L-2H with Docker Model Runner:
docker model run hf.co/arithmetic-circuit-overloading/gpt2-64D-1L-2H
- Xet hash:
- fd83108c3b72a46e30fd8ce1fd0054e8964a3c0116619abfaadaa9544bbaad15
- Size of remote file:
- 5.33 kB
- SHA256:
- d5ee64f64f72c667082895b7d4c8bc9ae88689b1ea7e4b8e18003cd7e37b8abf
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