Transformers
Safetensors
t5
text2text-generation
Generated from Trainer
Eval Results (legacy)
text-generation-inference
Instructions to use ayeshgk/codet5-small-java-v1-text-to-code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ayeshgk/codet5-small-java-v1-text-to-code with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ayeshgk/codet5-small-java-v1-text-to-code") model = AutoModelForSeq2SeqLM.from_pretrained("ayeshgk/codet5-small-java-v1-text-to-code") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6e17a4154b2a447211002748a08f6ee9c009a375bf2fd1e0a6ad404768f8e464
- Size of remote file:
- 4.86 kB
- SHA256:
- 4baee0216a064ec95e13f10ef95430b09a621d3d55de052e2b5859ed8a341086
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.