Instructions to use luminoria/fine_tuned_t5_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use luminoria/fine_tuned_t5_model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("luminoria/fine_tuned_t5_model") model = AutoModelForSeq2SeqLM.from_pretrained("luminoria/fine_tuned_t5_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from luminoria/fine_tuned_t5_model: direct link, hf CLI and curl.
- Browser
- Download file 242 MB
-
https://huggingface.co/luminoria/fine_tuned_t5_model/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://luminoria/fine_tuned_t5_model/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/luminoria/fine_tuned_t5_model/resolve/main/pytorch_model.bin
242 MB
- Xet hash:
- 7b93055390971c247de44b5f324a4c3afce5d28137f7b7af7f645a68d2cea9c7
- Size of remote file:
- 242 MB
- SHA256:
- 55469d87f2ff4c29785c5d8c200dd690d970ce3fb2be68ee09e28fbd023f88a8
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.