Instructions to use michaelnath/glued_code_to_code_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use michaelnath/glued_code_to_code_model with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("michaelnath/glued_code_to_code_model") model = AutoModelForSeq2SeqLM.from_pretrained("michaelnath/glued_code_to_code_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b28109cb2b13c5307eac0e89652f44e112ec5ca4923b26d1fd989a6c99d3910d
- Size of remote file:
- 892 MB
- SHA256:
- c636e2351f78d120c6c36c89e24c740bc4a98c95565dd3b3ba2859622ab16952
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