Instructions to use mtzig/reversemult_lr5e-4_batch128_train1-16_eval17 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mtzig/reversemult_lr5e-4_batch128_train1-16_eval17 with Transformers:
# Load model directly from transformers import NanoGPT model = NanoGPT.from_pretrained("mtzig/reversemult_lr5e-4_batch128_train1-16_eval17", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- d6b252a70c31dce7b6e568835bf08f6c2bb544ff04080cffe80617aa94c89706
- Size of remote file:
- 42.6 MB
- SHA256:
- 84a1d8d00df71509e41a80a2d5dd9e782ec5a8f588ce7baf0dc9e2d76f7c70af
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