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:
# Load model directly from transformers import PeptEdgeV2 model = PeptEdgeV2.from_pretrained("devansh0703/PeptEdgeV2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Initial release: PeptEdgeV2 (3.43M params) w/ trained weights, config, source, model card
9f16c4c verified | { | |
| "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" | |
| } |