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Show synchronized Dense/Veda R2VA comparisons with speedups in title bars
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{
"format": "miowtion-veda-predictor-v1",
"model_type": "veda_tile_score_predictor",
"weights_file": "minimax_h3_r2va_veda_preview_fp8.safetensors",
"base_model": "MiniMaxAI/MiniMax-H3",
"task": "reference-to-audio-video",
"variant": "Ref2VA",
"num_layers": 50,
"num_heads": 56,
"head_dim": 128,
"tile_size": 128,
"dtype": "float8_e4m3fn",
"target_budget_kind": "tiles",
"target_budget_value": 32,
"ref_budget_kind": "tiles",
"ref_budget_value": 32,
"tile_conditions": true,
"num_inference_steps": 8,
"geometries": {
"16x9_t102": {
"latent_grid": [
102,
24,
42
],
"tile_shapes": [
"8x4x4",
"2x8x8",
"4x8x4",
"8x8x2"
]
},
"16x9_t37": {
"latent_grid": [
37,
24,
42
],
"tile_shapes": [
"8x4x4",
"2x8x8",
"4x8x4",
"8x8x2"
]
},
"16x9_t72": {
"latent_grid": [
72,
24,
42
],
"tile_shapes": [
"8x4x4",
"2x8x8",
"4x4x8",
"4x8x4",
"8x8x2"
]
},
"1x1_t102": {
"latent_grid": [
102,
24,
24
],
"tile_shapes": [
"8x4x4",
"2x8x8",
"4x4x8",
"4x8x4",
"8x8x2",
"8x2x8"
]
},
"1x1_t37": {
"latent_grid": [
37,
24,
24
],
"tile_shapes": [
"8x4x4",
"2x8x8",
"4x4x8",
"8x8x2",
"8x2x8"
]
},
"1x1_t72": {
"latent_grid": [
72,
24,
24
],
"tile_shapes": [
"8x4x4",
"2x8x8",
"4x4x8",
"4x8x4",
"8x8x2",
"8x2x8"
]
},
"4x3_t102": {
"latent_grid": [
102,
24,
32
],
"tile_shapes": [
"8x4x4",
"2x8x8",
"4x4x8",
"4x8x4",
"8x8x2",
"8x2x8"
]
},
"4x3_t37": {
"latent_grid": [
37,
24,
32
],
"tile_shapes": [
"8x4x4",
"2x8x8",
"4x4x8",
"4x8x4",
"8x8x2",
"8x2x8"
]
},
"4x3_t72": {
"latent_grid": [
72,
24,
32
],
"tile_shapes": [
"8x4x4",
"2x8x8",
"4x4x8",
"4x8x4",
"8x8x2",
"8x2x8"
]
},
"9x16_t102": {
"latent_grid": [
102,
42,
24
],
"tile_shapes": [
"8x4x4",
"2x8x8",
"4x4x8",
"8x2x8"
]
},
"9x16_t37": {
"latent_grid": [
37,
42,
24
],
"tile_shapes": [
"8x4x4",
"2x8x8",
"4x4x8",
"8x2x8"
]
},
"9x16_t72": {
"latent_grid": [
72,
42,
24
],
"tile_shapes": [
"8x4x4",
"2x8x8",
"4x8x4",
"4x4x8",
"8x2x8"
]
}
},
"scale_suffix": ".__scale",
"scale_granularity": "per_head_amax",
"load_dtype": "bfloat16",
"compute_dtype": "float32",
"few_step_lora": "trained with Turbo 8 NFE; other schedules need validation",
"training": {
"stage": "tile-score predictor distillation",
"initialization": "T2VA predictor EMA",
"updates_r2va_finetuning": 600,
"training_conditions": 1000,
"trained_geometries": [
"16:9",
"9:16",
"4:3",
"1:1"
],
"trained_latent_t": [
37
],
"export": "live",
"backbone_frozen": true
}
}