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
File size: 241 Bytes
9f16c4c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | {
"vocab_size": 21,
"max_len": 200,
"d_model": 192,
"n_heads": 6,
"num_layers": 5,
"ff_dim": 384,
"num_classes": 2,
"dropout": 0.25,
"sd_prob": 0.05,
"architectures": [
"PeptEdgeV2"
],
"model_type": "peptedgev2"
} |