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:
- fadc97c6e9019519203ec80108067de8f96423c0f88ad93b4cea37de9912306b
- Size of remote file:
- 3.31 kB
- SHA256:
- dde0bfb523545e9635fb00e26a34d097a3d7021b1f2e59e3608339c4a64bd421
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