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:
# 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 decoder_pytorch_model.bin from commaai/commavq-gpt2m: direct link, hf CLI and curl.
- Browser
- Download file 171 MB
-
https://huggingface.co/commaai/commavq-gpt2m/resolve/main/decoder_pytorch_model.bin
- Command line
-
hf download hf://commaai/commavq-gpt2m/decoder_pytorch_model.bin
-
curl -L -o decoder_pytorch_model.bin https://huggingface.co/commaai/commavq-gpt2m/resolve/main/decoder_pytorch_model.bin
171 MB
- Xet hash:
- 9f3257605744c155506fefe30f2c07216f151a1e4ae2748f3b2371e51acf15be
- Size of remote file:
- 171 MB
- SHA256:
- 8bf91436802a38e28e16c3c53d90cd718bd12a4f33fcf385f2b4af85db61f0ee
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