Transformers
TensorBoard
Safetensors
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use cheaptrix/TokenizerTestingMTSUFall2024SoftwareEngineering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cheaptrix/TokenizerTestingMTSUFall2024SoftwareEngineering with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("cheaptrix/TokenizerTestingMTSUFall2024SoftwareEngineering") model = AutoModelForSeq2SeqLM.from_pretrained("cheaptrix/TokenizerTestingMTSUFall2024SoftwareEngineering") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f57b7c1534ce859c6d4e45324619420e71eddf10339268f960b53c95e12f1699
- Size of remote file:
- 242 MB
- SHA256:
- acb0ea91282ffbd724d259a2c3ebd545f7b40b4af345099e902a82e85e99918a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.