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")# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from NbAiLabArchive/test_NCC_small_flax: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/NbAiLabArchive/test_NCC_small_flax/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://NbAiLabArchive/test_NCC_small_flax/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/NbAiLabArchive/test_NCC_small_flax/resolve/main/flax_model.msgpack
499 MB
- Xet hash:
- ef8398c9e733cc0805f84666966d904bc9b7f6cc6278d774c07d3f1864523e7e
- Size of remote file:
- 499 MB
- SHA256:
- 8001dea0b9e5ae026ed2f7469e24632936d32dd493f0632fd8cb8c1f4e46de95
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