Transformers
PyTorch
TensorBoard
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use lmeninato/flan-t5-small-codesearchnet-python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lmeninato/flan-t5-small-codesearchnet-python with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("lmeninato/flan-t5-small-codesearchnet-python") model = AutoModelForSeq2SeqLM.from_pretrained("lmeninato/flan-t5-small-codesearchnet-python", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-4500/optimizer.pt from lmeninato/flan-t5-small-codesearchnet-python: direct link, hf CLI and curl.
- Browser
- Download file 1.14 MB
-
https://huggingface.co/lmeninato/flan-t5-small-codesearchnet-python/resolve/main/checkpoint-4500/optimizer.pt
- Command line
-
hf download hf://lmeninato/flan-t5-small-codesearchnet-python/checkpoint-4500/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/lmeninato/flan-t5-small-codesearchnet-python/resolve/main/checkpoint-4500/optimizer.pt
1.14 MB
- Xet hash:
- 52f13760bc51b3b2e4eec457747c2c7f2dbb8ea8fa5061f86712e92cc7650914
- Size of remote file:
- 1.14 MB
- SHA256:
- 38d2b1675cf84c9c78e10c7adb7c8c4bb5f9cb829915b8ae00f0d3a42cf80684
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.