Instructions to use michaelnath/scrappy_code_to_code_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michaelnath/scrappy_code_to_code_model with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("michaelnath/scrappy_code_to_code_model") model = AutoModelForSeq2SeqLM.from_pretrained("michaelnath/scrappy_code_to_code_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 84b29fb279bd6b729fe8e29e1dfd78411124e9af547279ce54dc21143a29461c
- Size of remote file:
- 892 MB
- SHA256:
- 4ab97e1c734bf0fec50238dd586e1e07f0cffc262aec370e70fc5dae9133cef9
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