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seungwonwonwon/
CNNED-Protein

Name: CNNED-Protein
Rating: 2.5 (5 reviews)

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CNNED_Protein

CNN-based embedding model for protein/bio sequences (triplet/contrastive training ready).

Model Summary

Input: one-hot encoded sequence of shape (B, A, L)
Encoder: 1D CNN + AvgPooling stacks
Output: L2-normalized embedding (B, D) via projection head
Training: Designed for triplet/contrastive loss (anchor, positive, negative)

Config

alphabet_size: 27
target_size: 128
channel: 256
depth: 3
kernel_size: 7
l2norm: True

Usage

python

import json, torch
from safetensors.torch import load_file

# Load config
cfg = json.load(open("config.json","r"))
from model import CNNED_Protein
model = CNNED_Protein(**cfg).eval()

# Load weights
try:
    sd = load_file("model.safetensors")
except Exception:
    sd = torch.load("model.pt", map_location="cpu")
model.load_state_dict(sd, strict=True)
model.eval()

# Dummy inference
# x: (B, A, L) one-hot tensor
x = torch.randn(2, cfg['alphabet_size'], 512)
y, z = model.encode(x)
print(y.shape)  # (2, target_size)

seungwonwonwon/CNNED-Protein

CNNED_Protein

Model Summary

Config

Usage

seungwonwonwon/
CNNED-Protein