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")# pip install -U transformers accelerate # 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
Download pytorch_model.bin from NbAiLabArchive/test_w5_long: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/NbAiLabArchive/test_w5_long/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://NbAiLabArchive/test_w5_long/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/NbAiLabArchive/test_w5_long/resolve/main/pytorch_model.bin
499 MB
- Xet hash:
- 5cd68a37487cd13af567f71bc165b99ed77509cea19dfaee4ac0a264c6cd528a
- Size of remote file:
- 499 MB
- SHA256:
- 8d99e1d2270cc3994a8b68d4115792c8bfc99b967a6b0917f5db220e5ebfbf32
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