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:
- 5fc66d246ba616888375ddd9eb891f3bd7a0323babf8cb84a015d0018bdd091c
- Size of remote file:
- 2.29 kB
- SHA256:
- 510ff08a80f765de97438a201e06b3f85f8e11e27979d06fdad577b891b88847
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