Instructions to use TheLongSentance/t5_large_baseline with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheLongSentance/t5_large_baseline with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("TheLongSentance/t5_large_baseline") model = AutoModelForSeq2SeqLM.from_pretrained("TheLongSentance/t5_large_baseline", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from TheLongSentance/t5_large_baseline: direct link, hf CLI and curl.
- Browser
- Download file 2.95 GB
-
https://huggingface.co/TheLongSentance/t5_large_baseline/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://TheLongSentance/t5_large_baseline/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/TheLongSentance/t5_large_baseline/resolve/main/pytorch_model.bin
2.95 GB
- Xet hash:
- 995a3ec58999e295e2096f1da57733e36af070935cedddbae2c3a7f923374149
- Size of remote file:
- 2.95 GB
- SHA256:
- 285242cc3d05861a28c2fe748418416dd6678008f8509e226f6433a491bca3a6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.