Instructions to use abhi11nav/F-CodeT5_ADC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abhi11nav/F-CodeT5_ADC with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("abhi11nav/F-CodeT5_ADC") model = AutoModelForSeq2SeqLM.from_pretrained("abhi11nav/F-CodeT5_ADC", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c84087edb0f07a678fbbe51d3f6a88f1e199e6febfe1745d5005f412e53e1138
- Size of remote file:
- 2.95 GB
- SHA256:
- 062509205c9f39e63a39aee4af9221d54390ef66460ba1113d6dc12e64739c00
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