Instructions to use NbAiLabArchive/test_NCC_small_flax_stream_100 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/test_NCC_small_flax_stream_100 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NbAiLabArchive/test_NCC_small_flax_stream_100")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NbAiLabArchive/test_NCC_small_flax_stream_100") model = AutoModelForMaskedLM.from_pretrained("NbAiLabArchive/test_NCC_small_flax_stream_100") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1b1cbae5a84fd1683ffc251834443944591501a1b23715f1d293d071fdae17dd
- Size of remote file:
- 499 MB
- SHA256:
- a8ffb61e9a1575545bd8904df7e4e0462c21f44e7d7b1558007bc848b64a08bd
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