[Feature]Add Data-free distillation readme (#710)
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@@ -6,7 +6,7 @@ We introduce a new finetuning strategy - **Sparse-distill**, which jointly integ
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We provide two distilled models:
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- **[FastWan2.1-T2V-1.3B-Diffusers](https://huggingface.co/FastVideo/FastWan2.1-T2V-1.3B-Diffusers)**: 3-step inference, up to **20 FPS** on H100 GPU
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- **[FastWan2.1-T2V-1.3B-Diffusers](https://huggingface.co/FastVideo/FastWan2.1-T2V-1.3B-Diffusers)**: 3-step inference, up to **16 FPS** on H100 GPU
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- **[FastWan2.1-T2V-14B-480P-Diffusers](https://huggingface.co/FastVideo/FastWan2.1-T2V-14B-480P-Diffusers)**: 3-step inference, up to **60x speed up** at 480P, **90x speed up** at 720P for denoising loop
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- **[FastWan2.2-TI2V-5B-FullAttn-Diffusers](https://huggingface.co/FastVideo/FastWan2.2-TI2V-5B-FullAttn-Diffusers)**: 3-step inference, up to **50x speed up** at 720P for denoising loop
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@@ -53,3 +53,9 @@ out = sliding_tile_attention(q, k, v, window_size, text_length)
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out = sliding_tile_attention(q, k, v, window_size, 0, False)
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```
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# 🚀Inference
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```bash
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bash scripts/inference/v1_inference_wan_STA.sh
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```
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@@ -59,3 +59,9 @@ from vsa import video_sparse_attn
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output = video_sparse_attn(q, k, v, variable_block_sizes, topk, block_size, compress_attn_weight)
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```
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# 🚀Inference
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```bash
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bash scripts/inference/v1_inference_wan_VSA.sh
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```
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