Instructions to use NbAiLabArchive/test_w8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/test_w8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NbAiLabArchive/test_w8")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NbAiLabArchive/test_w8") model = AutoModelForMaskedLM.from_pretrained("NbAiLabArchive/test_w8") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 27e4b83ec7e26b724760608874a9400997d6f62840b2f4181d7742d0ae8df7ca
- Size of remote file:
- 499 MB
- SHA256:
- fa5cbba936c3861c8bddc302f9ffb8b7b288d3c6d7ad5681cd5675b093b6b305
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