Diffusers
Safetensors
MiniMax H3
video-generation
reference-to-video
text-to-audio-video
fastvideo
fasth3-omni
nvfp4
qad
Instructions to use FastVideo/FastH3-Omni-NVFP4-QAD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use FastVideo/FastH3-Omni-NVFP4-QAD with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("FastVideo/FastH3-Omni-NVFP4-QAD", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
File size: 1,727 Bytes
3334982 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 | {
"name": "FastH3 NVFP4 VAE decoder (quality-36L)",
"format": "fastvideo_h3_decoder_nvfp4_deploy_v1",
"architecture": "MiniMaxH3VideoViTDecoder3d",
"decoder_blocks": 36,
"hidden_size": 2048,
"nvfp4": {
"scheme": "W4A4 NVFP4 (E2M1 values, E4M3 per-16 block scales, FP32 per-tensor scale)",
"block_size": 16,
"activation_global_scale": "unit",
"rotation_group": null,
"quantized_linears": 216,
"quantized_layers": "transformer_blocks.*.{attn.to_q,attn.to_k,attn.to_v,attn.to_out.0,ff.net.0.proj,ff.net.2}",
"high_precision": "proj_in, proj_out, norms, register tokens, post_quant_conv"
},
"compute_dtype": "bfloat16 autocast",
"host_vae": "MiniMaxAI/MiniMax-H3 vae/ (full 36-block VAE)",
"tensor_count_by_dtype": {
"float32": 369,
"bfloat16": 432
},
"nvfp4_linear_parameters": 2416877568,
"source_step": 6000,
"files": {
"decoder.safetensors": {
"format": "fastvideo_h3_decoder_nvfp4_deploy_v1",
"contents": "NVFP4 linears as bf16 master weights, packed to NVFP4 at load; other tensors in their trained dtype",
"bytes": 4860464512,
"use": "reference weights, re-quantization, further training"
},
"decoder-nvfp4.safetensors": {
"format": "fastvideo_h3_decoder_nvfp4_packed_v1",
"contents": "pre-packed NVFP4: per linear packed_weight (uint8, two E2M1 codes per byte), weight_inv_scale (E4M3 per-16 block scales, FlashInfer SfLayout.layout_128x4 swizzle), weight_global_sf (fp32), bias (bf16), input_amax (fp32); other tensors in their trained dtype (fp32)",
"bytes": 1387637112,
"use": "smallest download and lowest load memory; Blackwell only; decodes bit-identically to decoder.safetensors"
}
}
}
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