Instructions to use peterjandre/codet5-vbnet-csharp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use peterjandre/codet5-vbnet-csharp with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("peterjandre/codet5-vbnet-csharp") model = AutoModelForSeq2SeqLM.from_pretrained("peterjandre/codet5-vbnet-csharp", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 7d3580c1da28c46c9ef54495ef476e8c462a7408cc8699df28b9fc0bd1499a48
- Size of remote file:
- 892 MB
- SHA256:
- 9f41e01b29edee44759e6078d5722e6566f6c5fcddddae25e61b7f3741ce94f4
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