Unconditional Image Generation
Transformers
PyTorch
ONNX
gpt2
text-generation
text-generation-inference
Instructions to use commaai/commavq-gpt2m with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use commaai/commavq-gpt2m with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("commaai/commavq-gpt2m") model = AutoModelForCausalLM.from_pretrained("commaai/commavq-gpt2m", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download encoder_pytorch_model.bin from commaai/commavq-gpt2m: direct link, hf CLI and curl.
- Browser
- Download file 119 MB
-
https://huggingface.co/commaai/commavq-gpt2m/resolve/main/encoder_pytorch_model.bin
- Command line
-
hf download hf://commaai/commavq-gpt2m/encoder_pytorch_model.bin
-
curl -L -o encoder_pytorch_model.bin https://huggingface.co/commaai/commavq-gpt2m/resolve/main/encoder_pytorch_model.bin
119 MB
- Xet hash:
- c1c679bea3d8b3496d1da8d4643b59de8951638b2fb1d5ddddf51317bd437166
- Size of remote file:
- 119 MB
- SHA256:
- 9aefd8719991c1c503ad4266f8a45a2a33a042ccd4cbdfffe321c8d41f5ea183
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