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 temporal_decoder.onnx from commaai/commavq-gpt2m: direct link, hf CLI and curl.
- Browser
- Download file 310 MB
-
https://huggingface.co/commaai/commavq-gpt2m/resolve/main/temporal_decoder.onnx
- Command line
-
hf download hf://commaai/commavq-gpt2m/temporal_decoder.onnx
-
curl -L -o temporal_decoder.onnx https://huggingface.co/commaai/commavq-gpt2m/resolve/main/temporal_decoder.onnx
310 MB
- Xet hash:
- 2b5a0794fba065f3c8cc0ba3c85b5b4b1b4e50506ab2ec0d6123d1dae7cf1b1f
- Size of remote file:
- 310 MB
- SHA256:
- 1972bd8ba0a78591db9af6093c9cc0f6a083e29f948a7136b7c6a46fa9dbb4d2
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