Instructions to use michaelnath/dummy_code_to_code_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michaelnath/dummy_code_to_code_model with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("michaelnath/dummy_code_to_code_model") model = AutoModelForSeq2SeqLM.from_pretrained("michaelnath/dummy_code_to_code_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bd4a1476e9dcd12fdc5c66719c3bc85e3c7c8c02024ec95c44e9cfb3dc565ff3
- Size of remote file:
- 892 MB
- SHA256:
- fca4451b70df579b80713235d1654e65e6df438a9ce9af8e1800a926d424fb06
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