Transformers
PyTorch
TensorBoard
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use lmeninato/t5-small-codesearchnet-python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lmeninato/t5-small-codesearchnet-python with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("lmeninato/t5-small-codesearchnet-python") model = AutoModelForSeq2SeqLM.from_pretrained("lmeninato/t5-small-codesearchnet-python", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 57e61196274d5951fa2f68ede2bdcac8ac28f2d6b607fe082bf06e0fa842c5cd
- Size of remote file:
- 839 kB
- SHA256:
- 6b9101cf28c439172f2aa3a55a34cc8351a82a95ac6e403d3474a36966b95f2c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.