Instructions to use Jinendra/code-t5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jinendra/code-t5 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Jinendra/code-t5") model = AutoModelForSeq2SeqLM.from_pretrained("Jinendra/code-t5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.gguf from Jinendra/code-t5: direct link, hf CLI and curl.
- Browser
- Download file 183 MB
-
https://huggingface.co/Jinendra/code-t5/resolve/main/model.gguf
- Command line
-
hf download hf://Jinendra/code-t5/model.gguf
-
curl -L -o model.gguf https://huggingface.co/Jinendra/code-t5/resolve/main/model.gguf
183 MB
- Xet hash:
- b346bc4694b301f41e5bae4e10703026ce455380f360451a8a211189b3ea6c0f
- Size of remote file:
- 183 MB
- SHA256:
- 7a80875dfcbf9ebb0e24b70bf50684a884140dbc5ab731ab01252c1e912673cc
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