Instructions to use afaji/fresh-2-layer-copa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use afaji/fresh-2-layer-copa with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForMultipleChoice tokenizer = AutoTokenizer.from_pretrained("afaji/fresh-2-layer-copa") model = AutoModelForMultipleChoice.from_pretrained("afaji/fresh-2-layer-copa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6ba520783901f6cff40c8de47117bcd132a163907049138153611e3591173406
- Size of remote file:
- 4.03 kB
- SHA256:
- 2e5ece48e8879c3a775993542b4b6c2060d69421eabd904be818bd7fdbe4f426
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.