Text Classification
Transformers
bert
biology
genomics
dna
variant-effect-prediction
dnabert
deepvregulome
transcription-factors
histone-modifications
ENCODE
Instructions to use duttaprat/DeepVRegulome with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use duttaprat/DeepVRegulome with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="duttaprat/DeepVRegulome")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("duttaprat/DeepVRegulome") model = AutoModelForSequenceClassification.from_pretrained("duttaprat/DeepVRegulome") - Notebooks
- Google Colab
- Kaggle
File size: 191 Bytes
8366bb3 | 1 2 3 4 5 | {
"model_type": "bert",
"architectures": ["BertForSequenceClassification"],
"_note": "Root config for HuggingFace download tracking. Load individual models using subfolder parameter."
} |