Instructions to use Peltarion/dnabert-distilbert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Peltarion/dnabert-distilbert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Peltarion/dnabert-distilbert")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Peltarion/dnabert-distilbert") model = AutoModelForMaskedLM.from_pretrained("Peltarion/dnabert-distilbert") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 026b6b9491b86863a2ebb458badb69faa7c5561437c4b8eceec640d9d80d85b9
- Size of remote file:
- 187 MB
- SHA256:
- 7ac8ae9d85c4e4ccddcf6dfb4bd74a770823b5a8cfd29a3883ba212b6127560e
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