Transformers
TensorBoard
Safetensors
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use nahidcs/TokenizerTestingMTSUFall2024SoftwareEngineering with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nahidcs/TokenizerTestingMTSUFall2024SoftwareEngineering with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("nahidcs/TokenizerTestingMTSUFall2024SoftwareEngineering") model = AutoModelForSeq2SeqLM.from_pretrained("nahidcs/TokenizerTestingMTSUFall2024SoftwareEngineering", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ae756a17850fe94178cfb60ec470af9a4bf393f025612fe05134a7c8a7e1c0f4
- Size of remote file:
- 5.05 kB
- SHA256:
- 516570c78392e9d224730ccd6509ad328c6b969ec708266f910ad62517c25f9a
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.