Instructions to use Salesforce/codet5-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Salesforce/codet5-base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Salesforce/codet5-base") model = AutoModelForSeq2SeqLM.from_pretrained("Salesforce/codet5-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Update README.md (#4)
Verified signature- Update README.md (bf2f6a32615352f04f5aa2457a6a303340aebc30) Co-authored-by: Wenzhuo Yang <yangwenz@users.noreply.huggingface.co>02cd2d3
-
Upload vocab.json
4078456 -
Upload tokenizer_config.json
aa01b14 -
Upload special_tokens_map.json
7317944 -
Upload added_tokens.json
6ad0634
-
Remove inference widget
1706aa9 -
Set model_max_length to 512
f44c778 -
Update code example
f23c18c
-
Update README.md
1a501f4 -
Improve model card
152ae46 -
Add link to code datasets
5fe3699 -
Add codet5 tag
1a4c722 -
Add downstream tasks
85ae120 -
First draft of model card
6f0f019 -
Upload all files
3c3c9f4 -
Add tokenizer files
4c2e66e -
First commit
825eae1 -
initial commit
dfef752