Transformers
TensorBoard
Safetensors
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use cheaptrix/MTSUSpring2025SoftwareEngineering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cheaptrix/MTSUSpring2025SoftwareEngineering with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("cheaptrix/MTSUSpring2025SoftwareEngineering") model = AutoModelForSeq2SeqLM.from_pretrained("cheaptrix/MTSUSpring2025SoftwareEngineering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a740d8d51aa69fe3dd14ed6fd90312ebec8f94636995f29705c3d871ab146727
- Size of remote file:
- 6.1 kB
- SHA256:
- ec74ee33007a4fc0d401e9662ed9697395fd22d7eeb816d59ed002ee4fd28ffa
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.