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 tokenizer.json from NbAiLabArchive/test_NCC_OSCAR_style_98w: direct link, hf CLI and curl.
- Browser
- Download file 1.39 MB
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https://huggingface.co/NbAiLabArchive/test_NCC_OSCAR_style_98w/resolve/ecaf4c0ee9782158366b5ba4caadf5cfc8c4a943/tokenizer.json
- Command line
-
hf download hf://NbAiLabArchive/test_NCC_OSCAR_style_98w@ecaf4c0ee9782158366b5ba4caadf5cfc8c4a943/tokenizer.json
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curl -L -o tokenizer.json https://huggingface.co/NbAiLabArchive/test_NCC_OSCAR_style_98w/resolve/ecaf4c0ee9782158366b5ba4caadf5cfc8c4a943/tokenizer.json
1.39 MB
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