Text Classification
Transformers
PyTorch
Safetensors
prokbert
bioinformatics
genomics
sequence embedding
genomic language models
nucleotide
dna-sequence
promoter-prediction
custom_code
Instructions to use neuralbioinfo/prokbert-mini-promoter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use neuralbioinfo/prokbert-mini-promoter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="neuralbioinfo/prokbert-mini-promoter", trust_remote_code=True)# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("neuralbioinfo/prokbert-mini-promoter", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Ctrl+K