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Sana-600M samples with rewards for the diffusion alignment workshop
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{
"model": "Efficient-Large-Model/Sana_600M_512px_diffusers",
"sampler": "SanaPipeline default (DPMSolverMultistep, flow)",
"steps": 20,
"guidance_scale": 4.5,
"resolution": 512,
"samples_per_prompt": 5,
"complex_human_instruction": true,
"max_sequence_length": 128,
"latent_shape": [
5,
32,
16,
16
],
"latent_dtype": "float16",
"latent_space": "model (x0 fed to the transformer)",
"vae_scaling_factor": 0.41407,
"prompt_embeds_shape": [
128,
2304
],
"prompt_embeds_dtype": "float16",
"prompt_attention_mask_dtype": "uint8",
"rewards": {
"ocr": "1 - (character edits to find the target text in the Qwen/Qwen3-VL-2B-Instruct transcription) / len(target)",
"pickscore": "yuvalkirstain/PickScore_v1, logit_scale * cos(image, prompt) (~ 15..25)",
"aesthetic": "LAION aesthetic predictor v2 (trl-lib/ddpo-aesthetic-predictor) on CLIP ViT-L/14 (~ 1..10)",
"clip": "100 * cos(image, prompt), openai/clip-vit-large-patch14"
},
"n_train": 2048,
"n_eval": 64,
"diffusers": "0.41.0",
"torch": "2.9.0+cu128"
}