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:
- a8101a510c7127fb8ba4f8150aa06c60fb526886ddacee0935c221feb349b129
- Size of remote file:
- 3.18 kB
- SHA256:
- cc404c334e57e09b300a971195a2ee9fdee7b7101081d6473717a61fa13787a4
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