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.onnx from commaai/commavq-gpt2m: direct link, hf CLI and curl.
- Browser
- Download file 171 MB
-
https://huggingface.co/commaai/commavq-gpt2m/resolve/main/decoder.onnx
- Command line
-
hf download hf://commaai/commavq-gpt2m/decoder.onnx
-
curl -L -o decoder.onnx https://huggingface.co/commaai/commavq-gpt2m/resolve/main/decoder.onnx
171 MB
- Xet hash:
- 6e836d11768ae3cc8fcccf867ee12565e4f9b6d785eb131ecfd03c82099b3168
- Size of remote file:
- 171 MB
- SHA256:
- 22d7f1d7c7de42a0d19689abac0c27c5c844eec98541552a8f8cd14542edefdc
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