Instructions to use medardif/long-t5-local-base_complete_dataset_V_1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use medardif/long-t5-local-base_complete_dataset_V_1.0 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("medardif/long-t5-local-base_complete_dataset_V_1.0") model = AutoModelForSeq2SeqLM.from_pretrained("medardif/long-t5-local-base_complete_dataset_V_1.0", device_map="auto") - Notebooks
- Google Colab
- Kaggle
long-t5-local-base_complete_dataset_V_1.0 / logs /1684767720.6776412 /events.out.tfevents.1684767720.40418e1bd333.384.1
- Xet hash:
- 1efb2032ae30ab05383f6874fef00dc16713ae24330e637bb73a730c8f7f9b5b
- Size of remote file:
- 5.98 kB
- SHA256:
- 09d1ad529f5c8118a5f324e6d9106ce1323137090fc0d2c7508457248ea27274
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