Instructions to use NbAiLabArchive/test_NCC_OSCAR_style with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/test_NCC_OSCAR_style with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NbAiLabArchive/test_NCC_OSCAR_style")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NbAiLabArchive/test_NCC_OSCAR_style") model = AutoModelForMaskedLM.from_pretrained("NbAiLabArchive/test_NCC_OSCAR_style", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from NbAiLabArchive/test_NCC_OSCAR_style: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/NbAiLabArchive/test_NCC_OSCAR_style/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://NbAiLabArchive/test_NCC_OSCAR_style/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/NbAiLabArchive/test_NCC_OSCAR_style/resolve/main/flax_model.msgpack
499 MB
- Xet hash:
- 52e9529a4856bde230f231bba1522ac00bb050517a92b5d210840daf5b5d74a2
- Size of remote file:
- 499 MB
- SHA256:
- 0385b8d395074b25a6efa6e7af24f07053d7eb7755fb3c853c3b2d7c6fab622b
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