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:
- 3e732debf0fd91cb561c18b5e5e65fbfabc367699a5be7fc4fe1d842de3e8c01
- Size of remote file:
- 242 MB
- SHA256:
- c99c16e2ef02d6d5365ae3baadb8f20e7419b934e1862a2834515712bd879818
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.