Instructions to use NbAiLabArchive/test_w6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/test_w6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NbAiLabArchive/test_w6")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NbAiLabArchive/test_w6") model = AutoModelForMaskedLM.from_pretrained("NbAiLabArchive/test_w6") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec975a9b5cfcadd071cbd3e41c26c4b55c49c2b38f15c99ef0eb11bcdb9327d5
- Size of remote file:
- 499 MB
- SHA256:
- 87ed4caaca4175ff744fdd2bf12b38691018652881be53e5d903798a9475c9e2
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