Transformers
PyTorch
TensorBoard
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use athugodage/T5-RLS2000 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use athugodage/T5-RLS2000 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("athugodage/T5-RLS2000") model = AutoModelForSeq2SeqLM.from_pretrained("athugodage/T5-RLS2000") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 74078149fda8be8e2bbb888f09862a749f19b4389f7538875a45d7b39230f234
- Size of remote file:
- 3.64 kB
- SHA256:
- 750cd526c6b54e683c723f0b19fbbc430e0c57377663e297f32267ef83f04012
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.