Instructions to use NbAiLabArchive/test_w5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/test_w5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NbAiLabArchive/test_w5")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NbAiLabArchive/test_w5") model = AutoModelForMaskedLM.from_pretrained("NbAiLabArchive/test_w5") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 800c5794b2c05e284ad046c4273bebcdb06ea939aa4d8267ecebd44a77ca017c
- Size of remote file:
- 499 MB
- SHA256:
- 0c0ef99d6b6e1a47ad00474100dd3a3c9c17c8cec41fde77b1252184054f2168
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