Instructions to use NbAiLabArchive/test_w5_long with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/test_w5_long with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NbAiLabArchive/test_w5_long")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NbAiLabArchive/test_w5_long") model = AutoModelForMaskedLM.from_pretrained("NbAiLabArchive/test_w5_long", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b50ad0338dd4afbd854b75ed122994e1e015c062746ddcdfee9c967e7240df32
- Size of remote file:
- 499 MB
- SHA256:
- da72f2eea1b3a767bc9a505306c985c7462ef8495816ebe5e4d904deaa834d2d
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