Instructions to use simecek/DNADebertaK7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simecek/DNADebertaK7b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="simecek/DNADebertaK7b")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("simecek/DNADebertaK7b") model = AutoModelForMaskedLM.from_pretrained("simecek/DNADebertaK7b") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 366701f0fd34c7a5d911c95fecf86d80df6104d985978dfd31ce43f2a2a77b68
- Size of remote file:
- 237 MB
- SHA256:
- 82c9a152d4b976b5490603fffb7bc9f250e5f4fc6cf966cfc35a79a3f6713006
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