Training Slayer V740 By Bokundev High Quality Apr 2026

# Set hyperparameters num_classes = 8 input_dim = 128 batch_size = 32 epochs = 10 lr = 1e-4

import torch import torch.nn as nn import torch.optim as optim from torch.utils.data import Dataset, DataLoader training slayer v740 by bokundev high quality

# Define the Slayer V7.4.0 model class SlayerV7_4_0(nn.Module): def __init__(self, num_classes, input_dim): super(SlayerV7_4_0, self).__init__() self.encoder = nn.Sequential( nn.Conv1d(input_dim, 128, kernel_size=3), nn.ReLU(), nn.MaxPool1d(2), nn.Flatten() ) self.decoder = nn.Sequential( nn.Linear(128, num_classes), nn.Softmax(dim=1) ) # Set hyperparameters num_classes = 8 input_dim =

# Initialize model, optimizer, and loss function model = SlayerV7_4_0(num_classes, input_dim) optimizer = optim.Adam(model.parameters(), lr=lr) criterion = nn.CrossEntropyLoss() nn.Flatten() ) self.decoder = nn.Sequential( nn.Linear(128