MOBOLAJI
Model description
from transformers import MOBOLAJI
Define your dataset and dataloader
dataset = YourDataset()
dataloader = DataLoader(dataset, batch_size=32, shuffle=True)
Define optimizer
optimizer = MOBOLAJI (model.parameters(), lr=5e-5)
Fine-tuning loop
model.train() for epoch in range(num_epochs): for batch in dataloader: optimizer.zero_grad() inputs = tokenizer(batch['text'], return_tensors='pt', padding=True, truncation=True) outputs = model(**inputs) loss = compute_loss(outputs, batch['labels']) loss.backward() optimizer.step()
Trigger words
You should use MOBOLAJI
to trigger the image generation.
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Model tree for adedolllapo/MOBOLAJI
Base model
stabilityai/stable-diffusion-3-medium