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") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cccfafd367fffc8a390db46855026cebaf5c9ca2635c3c918b15cac0ba014bf5
- Size of remote file:
- 892 MB
- SHA256:
- 527e3c85a7871867111b9ed4edba74056db74132159136004ba6c159c241b2aa
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