Instructions to use mtzig/gpt2_cfg_add_8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mtzig/gpt2_cfg_add_8 with Transformers:
# Load model directly from transformers import NanoGPT model = NanoGPT.from_pretrained("mtzig/gpt2_cfg_add_8", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 422cca2fac3d6e5f58898cedb892dbc92842a2fc02ee3a2d731f2916e4c1e65b
- Size of remote file:
- 5.18 kB
- SHA256:
- 9cf2427c9da03e58124d55de2bd74f3b1e6618a0e32595560014fe30aad05a1f
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