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:
- 8cf0d0cc8a6d5e62c2f381a2acc93dc378a2a78d02c8cec0f55fbd51054d55dc
- Size of remote file:
- 242 MB
- SHA256:
- 75281f36562efadb25ef4ed35b4be1f8d790d093c7572e97a8d39eac3216704e
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.