Instructions to use simecek/DNADebertaBPE30k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use simecek/DNADebertaBPE30k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="simecek/DNADebertaBPE30k")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("simecek/DNADebertaBPE30k") model = AutoModelForMaskedLM.from_pretrained("simecek/DNADebertaBPE30k") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 29fce0ce150909dfeb580854dddfd1256846c721eb2e35a6bba53ce0464dd2ef
- Size of remote file:
- 266 MB
- SHA256:
- 9a19540923c83603fe3b5b5ec5ab754b31ce055c4dd7d0d7f294b075b22e5041
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