Safetensors
PyTorch
Transformers
custom
peptedgev2
biology
bioinformatics
peptides
protein
antimicrobial-peptide
amp
protein-sequence
sequence-classification
Eval Results (legacy)
Instructions to use devansh0703/PeptEdgeV2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devansh0703/PeptEdgeV2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import PeptEdgeV2 model = PeptEdgeV2.from_pretrained("devansh0703/PeptEdgeV2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Remove misleading text-classification pipeline/task tags; use protein-sequence task
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Link HF dataset (devansh0703/GenPept-Curated-2025) + add dataset citation/license
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Delete files *.pyc with huggingface_hub
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Initial release: PeptEdgeV2 (3.43M params) w/ trained weights, config, source, model card
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initial commit
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