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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 916bad87fedfd97eff1516ed11839745102ee5b9d0a8610c25ed4ccdd2684172
- Size of remote file:
- 499 MB
- SHA256:
- c7af28dec723de6c40fb71f8137888df28b65a2c852d5ef0a1861f7a8209c667
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