Instructions to use melll-uff/itd_longformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use melll-uff/itd_longformer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="melll-uff/itd_longformer")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("melll-uff/itd_longformer") model = AutoModelForMaskedLM.from_pretrained("melll-uff/itd_longformer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9fa74f92e24bd71565d72a33ed0343f8fa26b9850ffeaf6ca98618e206ec8947
- Size of remote file:
- 447 MB
- SHA256:
- 6295c448cba660619cd40c1c5268ddedeb79ecaedbd7357b4d8f9e79c589e371
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