Instructions to use NbAiLabArchive/test_w5_long_dataset with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/test_w5_long_dataset with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NbAiLabArchive/test_w5_long_dataset")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NbAiLabArchive/test_w5_long_dataset") model = AutoModelForMaskedLM.from_pretrained("NbAiLabArchive/test_w5_long_dataset", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e74a05901cf87ab3532b043a5018e0c8d3d15dafbb88e0ace310880986699428
- Size of remote file:
- 499 MB
- SHA256:
- 35a2b20cdf420aabe5b7b01c5498c89a7aaa7847500d730100a3b373875cea1a
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