Instructions to use lmeninato/t5-small-codesearchnet-python-archive with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lmeninato/t5-small-codesearchnet-python-archive with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("lmeninato/t5-small-codesearchnet-python-archive") model = AutoModelForSeq2SeqLM.from_pretrained("lmeninato/t5-small-codesearchnet-python-archive", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c33d2d93142158deee4552b9e9d3b38b3c564b16749bda41859d83ad9c71e9ef
- Size of remote file:
- 3.58 kB
- SHA256:
- 533d95cbf8aea627be6c1763567c84c1c6bf7124979483027e8997950505a94f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.