Instructions to use NbAiLabArchive/test_NCC_OSCAR_style_98w with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/test_NCC_OSCAR_style_98w with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NbAiLabArchive/test_NCC_OSCAR_style_98w")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NbAiLabArchive/test_NCC_OSCAR_style_98w") model = AutoModelForMaskedLM.from_pretrained("NbAiLabArchive/test_NCC_OSCAR_style_98w", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from NbAiLabArchive/test_NCC_OSCAR_style_98w: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/NbAiLabArchive/test_NCC_OSCAR_style_98w/resolve/ecaf4c0ee9782158366b5ba4caadf5cfc8c4a943/flax_model.msgpack
- Command line
-
hf download hf://NbAiLabArchive/test_NCC_OSCAR_style_98w@ecaf4c0ee9782158366b5ba4caadf5cfc8c4a943/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/NbAiLabArchive/test_NCC_OSCAR_style_98w/resolve/ecaf4c0ee9782158366b5ba4caadf5cfc8c4a943/flax_model.msgpack
499 MB
- Xet hash:
- cf6dab4b2dc3f6a56c8e6c5ee08002b9d5c6f57c8bda985e70500c9d7ee58015
- Size of remote file:
- 499 MB
- SHA256:
- 0d42c0a552c30a4caa038a6e404f80ef4102e01b74f43ab853fc1eb4c99cbc19
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