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:
- 70d58bb6d0de2e14ebe638df6831c1595926183c63cdc3ca60bc862c5c91ceda
- Size of remote file:
- 5.5 kB
- SHA256:
- 9ca8382e4894ee57156dcb30b0d440afa3993ff4ef6e555b845a22ed79239d8d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.