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isl-unconditional-diffusion-128 – AI Model by mahadev-balla | AlphaNeural AI
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isl-unconditional-diffusion-128
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safetensors
image-generation
unconditional-diffusion
indian-sign-language
unconditional-image-generation
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ISL Unconditional Diffusion
An unconditional DDPM trained from scratch to generate 128×128 RGB images of Indian Sign Language hand gestures.
The model learns the overall distribution of ISL gesture images without receiving a class label during training or inference.
The complete implementation and experiments are available in the
GitHub repository
.
Model
DDPM with UNet2D architecture
128×128 resolution
RGB images
Unconditional generation
EMA weights
Training
Dataset: 42,000 images (1,200 images per class × 35 classes)
Noise schedule: cosine
Batch size: 64
Learning rate: 1e-4
Mixed precision: fp16
Training steps: 65,000
EMA decay: 0.9999
Data augmentation: enabled
Sampling
Default sampler: DDIM
Training diffusion timesteps: 1,000
Routine inference steps: 100
Evaluation inference steps: 50
Random seed: 42
Results
The unconditional model achieves an FID of 86.06 under the reported evaluation setting.
