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:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Salesforce/codet5-base") model = AutoModelForSeq2SeqLM.from_pretrained("Salesforce/codet5-base") - Notebooks
- Google Colab
- Kaggle
Add TF weights
#1
by mastro1996 - opened
Model converted by the transformers' pt_to_tf CLI. All converted model outputs and hidden layers were validated against its PyTorch counterpart.
Maximum crossload output difference=4.292e-06; Maximum crossload hidden layer difference=5.981e-03;
Maximum conversion output difference=4.292e-06; Maximum conversion hidden layer difference=5.981e-03;
CAUTION: The maximum admissible error was manually increased to 0.009!