Instructions to use NbAiLabArchive/test_OSCAR_flax with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/test_OSCAR_flax with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NbAiLabArchive/test_OSCAR_flax")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NbAiLabArchive/test_OSCAR_flax") model = AutoModelForMaskedLM.from_pretrained("NbAiLabArchive/test_OSCAR_flax", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from NbAiLabArchive/test_OSCAR_flax: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/NbAiLabArchive/test_OSCAR_flax/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://NbAiLabArchive/test_OSCAR_flax/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/NbAiLabArchive/test_OSCAR_flax/resolve/main/flax_model.msgpack
499 MB
- Xet hash:
- d79020aa0cf66ac18bf075e01947d6387d226aed310102d01960a7454fa0107e
- Size of remote file:
- 499 MB
- SHA256:
- 87d1908af15f8d9d4b42b84dc54a3da3a0e9cacd81ab71a9152bcd12bfbd3791
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