Transformers
PyTorch
TensorBoard
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use lmeninato/flan-t5-base-codesearchnet-python3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lmeninato/flan-t5-base-codesearchnet-python3 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("lmeninato/flan-t5-base-codesearchnet-python3") model = AutoModelForSeq2SeqLM.from_pretrained("lmeninato/flan-t5-base-codesearchnet-python3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8ea1bf67af28f6a4005d2e94eb4baaf2dbb8641f6ee12c43a93c6ae998ffee1e
- Size of remote file:
- 990 MB
- SHA256:
- 9b7d40c2cfc66ecce0a477c9c1f13f084511096b6202520dc8b875b872ea2a3d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.