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:
- 8407666c65f1c4f6fa0ab9ba675d93d3712b3955895ef6953d5e541a07d135d4
- Size of remote file:
- 242 MB
- SHA256:
- ed2ac53b7bd14f8b3050793a941b65e2c2f8e6d778dfedd5d8fd45aada50d8b7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.