Transformers
TensorBoard
Safetensors
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use syssec-utd/py38-pylingual-v1-statement with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use syssec-utd/py38-pylingual-v1-statement with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("syssec-utd/py38-pylingual-v1-statement") model = AutoModelForSeq2SeqLM.from_pretrained("syssec-utd/py38-pylingual-v1-statement") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- e0bb923ac2bacab7e5ec3010b59b0782e0767aa60e625f522a4e54c9c175d038
- Size of remote file:
- 5.62 kB
- SHA256:
- f0d0bbdfc64f525648875398c389ece57281e0052da2caf29480f40a377a311e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.