Transformers
PyTorch
TensorBoard
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use lmeninato/t5-small-codesearchnet-python3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lmeninato/t5-small-codesearchnet-python3 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("lmeninato/t5-small-codesearchnet-python3") model = AutoModelForSeq2SeqLM.from_pretrained("lmeninato/t5-small-codesearchnet-python3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 66b809e155c1730e5bb1c766de9e46da48f32824ffb4eaaaac52f8e6c64b12cc
- Size of remote file:
- 881 Bytes
- SHA256:
- a073918da88c5be793b4c33fd1b2186aef4d60f80af0c6e10687e6d64bdd2dd7
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.