Instructions to use NbAiLabArchive/test_NCC_small_flax with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/test_NCC_small_flax with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NbAiLabArchive/test_NCC_small_flax")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NbAiLabArchive/test_NCC_small_flax") model = AutoModelForMaskedLM.from_pretrained("NbAiLabArchive/test_NCC_small_flax") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ef8398c9e733cc0805f84666966d904bc9b7f6cc6278d774c07d3f1864523e7e
- Size of remote file:
- 499 MB
- SHA256:
- 8001dea0b9e5ae026ed2f7469e24632936d32dd493f0632fd8cb8c1f4e46de95
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