hao-ai-lab · HaripraveenS · Mar 4, 2026 · Mar 9, 2026
diff --git a/docs/contributing/coding_agents.md b/docs/contributing/coding_agents.md
@@ -145,13 +145,13 @@ Action:
 - Clone the official repo under the project root (e.g., `FastVideo/LTX-2/`).
 - If a Diffusers-format HF repo already exists, you can skip manual weight
   handling and download it directly with
-  `scripts/huggingface/download_hf.py`.
+  `examples/huggingface/download_hf.py`.
 
 !!! note
     This step is best done manually because large downloads can time out.
     Example:
     ```bash
-    python scripts/huggingface/download_hf.py \
+    python examples/huggingface/download_hf.py \
       --repo_id Wan-AI/Wan2.1-T2V-1.3B-Diffusers \
       --local_dir official_weights/Wan2.1-T2V-1.3B-Diffusers \
       --repo_type model
@@ -194,7 +194,7 @@ Action:
 !!! note
     If a Diffusers-format HF repo already exists and loads correctly, you can
     skip conversion entirely (no conversion script needed) and just download it
-    with `scripts/huggingface/download_hf.py`. Otherwise, you may need a
+    with `examples/huggingface/download_hf.py`. Otherwise, you may need a
     conversion script + a `converted_weights/<model>/` staging directory.
 
 Example (key renaming via arch config mapping, Wan2.1‑style):
@@ -418,7 +418,7 @@ If the model does **not** have a Diffusers-format repo:
 In both cases, parity testing is required to validate correctness.
 
 If you want to publish a Diffusers‑style repo after conversion, use
-`scripts/checkpoint_conversion/create_hf_repo.py` to assemble a HuggingFace‑ready
+`examples/checkpoint_conversion/create_hf_repo.py` to assemble a HuggingFace‑ready
 directory before uploading.
 
 ## FAQ

diff --git a/docs/distillation/data_preprocess.md b/docs/distillation/data_preprocess.md
@@ -11,7 +11,7 @@ For Wan2.1 T2V distillation, we use the **FastVideo 480P Synthetic Wan dataset**
 
 ```bash
 # Download the preprocessed dataset
-python scripts/huggingface/download_hf.py \
+python examples/huggingface/download_hf.py \
     --repo_id "FastVideo/Wan-Syn_77x448x832_600k" \
     --local_dir "FastVideo/Wan-Syn_77x448x832_600k" \
     --repo_type "dataset"
@@ -23,7 +23,7 @@ For Wan2.2 TI2V distillation, we use the crush_smol dataset which includes both
 
 ```bash
 # Download dataset
-python scripts/huggingface/download_hf.py \
+python examples/huggingface/download_hf.py \
     --repo_id=FastVideo/mini_i2v_dataset \
     --local_dir=data/mini_i2v_dataset \
     --repo_type=dataset
@@ -35,7 +35,7 @@ The preprocessing steps are identical to training. Run the appropriate preproces
 
 ```bash
 # For Wan2.1 T2V
-bash scripts/preprocess/v1_preprocess_wan_data_t2v
+bash examples/preprocessing/v1_preprocess_wan_data_t2v
 
 # For Wan2.2 TI2V  
 bash examples/distill/Wan2.2-TI2V-5B-Diffusers/crush_smol/preprocess_wan_data_ti2v_5b.sh

diff --git a/docs/distillation/dmd.md b/docs/distillation/dmd.md
@@ -16,7 +16,7 @@ Both models are trained on **61×448×832** resolution but support generating vi
 First install [VSA](../attention/vsa/index.md). Set `MODEL_BASE` to your own model path and run:
 
 ```bash
-bash scripts/inference/v1_inference_wan_dmd.sh
+bash examples/inference/cli/v1_inference_wan_dmd.sh
 ```
 
 ## 🗂️ Dataset
@@ -27,7 +27,7 @@ We use the **FastVideo 480P Synthetic Wan dataset** ([FastVideo/Wan-Syn_77x448x8
 
 ```bash
 # Download the preprocessed dataset
-python scripts/huggingface/download_hf.py \
+python examples/huggingface/download_hf.py \
     --repo_id "FastVideo/Wan-Syn_77x448x832_600k" \
     --local_dir "FastVideo/Wan-Syn_77x448x832_600k" \
     --repo_type "dataset"

diff --git a/docs/inference/inference_quick_start.md b/docs/inference/inference_quick_start.md
@@ -60,8 +60,7 @@ python example.py
 
 The generated video will be saved in the current directory under `my_videos/`  
 
-More inference scripts and recipes can be found in `examples/inference/` and
-`scripts/inference/`.
+More inference example scripts can be found in `examples/inference/cli/`
 
 ## Available Models
 

diff --git a/docs/training/data_preprocess.md b/docs/training/data_preprocess.md
@@ -8,7 +8,7 @@ Download the sample dataset and run preprocessing:
 
 ```bash
 # Download the crush-smol dataset
-python scripts/huggingface/download_hf.py \
+python examples/huggingface/download_hf.py \
     --repo_id "wlsaidhi/crush-smol-merged" \
     --local_dir "data/crush-smol" \
     --repo_type "dataset"
@@ -93,7 +93,7 @@ Use `--preprocess.dataset_type hf` and point `--preprocess.dataset_path` to a Hu
 If you have raw videos and captions in separate files, generate the `videos2caption.json`:
 
 ```bash
-python scripts/dataset_preparation/prepare_json_file.py \
+python examples/preprocessing/prepare_json_file.py \
     --data_folder path/to/your_raw_data/ \
     --output path/to/output_folder
 ```

diff --git a/docs/training/finetune.md b/docs/training/finetune.md
@@ -105,7 +105,7 @@ FastVideo provides tools to extract LoRA adapters from finetuned models and merg
 Extract a LoRA adapter by comparing a finetuned model to its base:
 
 ```bash
-python scripts/lora_extraction/extract_lora.py \
+python examples/lora_extraction/extract_lora.py \
   --base Wan-AI/Wan2.1-T2V-1.3B-Diffusers \
   --ft path/to/your/finetuned_model \
   --out adapter_r32.safetensors \
@@ -125,7 +125,7 @@ python scripts/lora_extraction/extract_lora.py \
 Merge an adapter back into a base model:
 
 ```bash
-python scripts/lora_extraction/merge_lora.py \
+python examples/lora_extraction/merge_lora.py \
   --base Wan-AI/Wan2.1-T2V-1.3B-Diffusers \
   --adapter adapter_r32.safetensors \
   --ft path/to/your/finetuned_model \
@@ -144,7 +144,7 @@ python scripts/lora_extraction/merge_lora.py \
 Compare the merged model against the original finetuned model:
 
 ```bash
-python scripts/lora_extraction/lora_inference_comparison.py \
+python examples/lora_extraction/lora_inference_comparison.py \
   --base merged_model \
   --ft path/to/your/finetuned_model \
   --adapter NONE \

diff --git a/docs/utilities/lora.md b/docs/utilities/lora.md
@@ -5,7 +5,7 @@ Tools for extracting and merging LoRA adapters for FastVideo models.
 ## Extract LoRA Adapter
 
 ```bash
-python scripts/lora_extraction/extract_lora.py \
+python examples/lora_extraction/extract_lora.py \
   --base Wan-AI/Wan2.2-TI2V-5B-Diffusers \
   --ft FastVideo/FastWan2.2-TI2V-5B-FullAttn-Diffusers \
   --out adapter_r32.safetensors \
@@ -23,7 +23,7 @@ python scripts/lora_extraction/extract_lora.py \
 ## Merge Adapter
 
 ```bash
-python scripts/lora_extraction/merge_lora.py \
+python examples/lora_extraction/merge_lora.py \
   --base Wan-AI/Wan2.2-TI2V-5B-Diffusers \
   --adapter adapter_r32.safetensors \
   --ft FastVideo/FastWan2.2-TI2V-5B-FullAttn-Diffusers \
@@ -40,7 +40,7 @@ python scripts/lora_extraction/merge_lora.py \
 ## Validate Quality (Optional)
 
 ```bash
-python scripts/lora_extraction/lora_inference_comparison.py \
+python examples/lora_extraction/lora_inference_comparison.py \
   --base merged_model \
   --ft FastVideo/FastWan2.2-TI2V-5B-FullAttn-Diffusers \
   --adapter NONE \

diff --git a/scripts/check_docs_links.py → examples/check_docs_links.py b/scripts/check_docs_links.py → examples/check_docs_links.py
diff --git a/...oint_conversion/convert_gamecraft_full.py → ...oint_conversion/convert_gamecraft_full.py b/...oint_conversion/convert_gamecraft_full.py → ...oint_conversion/convert_gamecraft_full.py
diff --git a/...point_conversion/convert_gamecraft_vae.py → ...point_conversion/convert_gamecraft_vae.py b/...point_conversion/convert_gamecraft_vae.py → ...point_conversion/convert_gamecraft_vae.py
diff --git a/...t_conversion/convert_gamecraft_weights.py → ...t_conversion/convert_gamecraft_weights.py b/...t_conversion/convert_gamecraft_weights.py → ...t_conversion/convert_gamecraft_weights.py
diff --git a/...kpoint_conversion/convert_ltx2_weights.py → ...kpoint_conversion/convert_ltx2_weights.py b/...kpoint_conversion/convert_ltx2_weights.py → ...kpoint_conversion/convert_ltx2_weights.py
diff --git a/...onvert_turbodiffusion_i2v_to_diffusers.py → ...onvert_turbodiffusion_i2v_to_diffusers.py b/...onvert_turbodiffusion_i2v_to_diffusers.py → ...onvert_turbodiffusion_i2v_to_diffusers.py
diff --git a/...on/convert_turbodiffusion_to_diffusers.py → ...on/convert_turbodiffusion_to_diffusers.py b/...on/convert_turbodiffusion_to_diffusers.py → ...on/convert_turbodiffusion_to_diffusers.py
@@ -194,7 +194,7 @@ def main():
     print(f"\nDone! Converted weights saved to: {args.output_dir}")
     print(f"\nNext steps:")
     print(f"  1. Use create_hf_repo.py to create a complete diffusers repo:")
-    print(f"     python scripts/checkpoint_conversion/create_hf_repo.py \\")
+    print(f"     python examples/checkpoint_conversion/create_hf_repo.py \\")
     print(f"       --repo_id Wan-AI/Wan2.1-T2V-1.3B-Diffusers \\")
     print(f"       --local_dir /tmp/turbodiffusion-wan \\")
     print(f"       --checkpoint_dir {args.output_dir} \\")

diff --git a/...s/checkpoint_conversion/create_hf_repo.py → ...s/checkpoint_conversion/create_hf_repo.py b/...s/checkpoint_conversion/create_hf_repo.py → ...s/checkpoint_conversion/create_hf_repo.py
diff --git a/..._conversion/extract_llava_text_encoder.py → ..._conversion/extract_llava_text_encoder.py b/..._conversion/extract_llava_text_encoder.py → ..._conversion/extract_llava_text_encoder.py
diff --git a/...kpoint_conversion/longcat_to_fastvideo.py → ...kpoint_conversion/longcat_to_fastvideo.py b/...kpoint_conversion/longcat_to_fastvideo.py → ...kpoint_conversion/longcat_to_fastvideo.py
@@ -12,7 +12,7 @@
 4. Updates config files to point to native model
 
 Usage:
-    python scripts/checkpoint_conversion/longcat_to_fastvideo.py \
+    python examples/checkpoint_conversion/longcat_to_fastvideo.py \
         --source /path/to/LongCat-Video/weights/LongCat-Video \
         --output weights/longcat-native \
         --validate

diff --git a/...heckpoint_conversion/pt_to_safetensors.py → ...heckpoint_conversion/pt_to_safetensors.py b/...heckpoint_conversion/pt_to_safetensors.py → ...heckpoint_conversion/pt_to_safetensors.py
diff --git a/...nt_conversion/validate_longcat_weights.py → ...nt_conversion/validate_longcat_weights.py b/...nt_conversion/validate_longcat_weights.py → ...nt_conversion/validate_longcat_weights.py
diff --git a/...checkpoint_conversion/wan_to_diffusers.py → ...checkpoint_conversion/wan_to_diffusers.py b/...checkpoint_conversion/wan_to_diffusers.py → ...checkpoint_conversion/wan_to_diffusers.py
diff --git a/examples/dataset/vidprom/README.md → examples/datasets/vidprom/README.md b/examples/dataset/vidprom/README.md → examples/datasets/vidprom/README.md
diff --git a/examples/dataset/vidprom/download_dataset.sh → ...ples/datasets/vidprom/download_dataset.sh b/examples/dataset/vidprom/download_dataset.sh → ...ples/datasets/vidprom/download_dataset.sh
diff --git a/examples/distill/SFWan2.1-T2V/download_dataset.sh b/examples/distill/SFWan2.1-T2V/download_dataset.sh
@@ -1,3 +1,3 @@
 #!/bin/bash
 
-python scripts/huggingface/download_hf.py --repo_id "wlsaidhi/crush-smol-merged" --local_dir "data/crush-smol" --repo_type "dataset"
+python examples/huggingface/download_hf.py --repo_id "wlsaidhi/crush-smol-merged" --local_dir "data/crush-smol" --repo_type "dataset"
diff --git a/examples/distill/Wan2.1-T2V/Wan-Syn-Data-480P/download_dataset.sh b/examples/distill/Wan2.1-T2V/Wan-Syn-Data-480P/download_dataset.sh
@@ -1,3 +1,3 @@
 #!/bin/bash
 
-python scripts/huggingface/download_hf.py --repo_id "FastVideo/Wan-Syn_77x448x832_600k" --local_dir "FastVideo/Wan-Syn_77x448x832_600k" --repo_type "dataset"
+python examples/huggingface/download_hf.py --repo_id "FastVideo/Wan-Syn_77x448x832_600k" --local_dir "FastVideo/Wan-Syn_77x448x832_600k" --repo_type "dataset"
diff --git a/examples/distill/Wan2.2-TI2V-5B-Diffusers/crush_smol/download_dataset.sh b/examples/distill/Wan2.2-TI2V-5B-Diffusers/crush_smol/download_dataset.sh
@@ -1,3 +1,3 @@
 #!/bin/bash
 
-python scripts/huggingface/download_hf.py --repo_id "wlsaidhi/crush-smol-merged" --local_dir "data/crush-smol" --repo_type "dataset"
+python examples/huggingface/download_hf.py --repo_id "wlsaidhi/crush-smol-merged" --local_dir "data/crush-smol" --repo_type "dataset"
diff --git a/scripts/distill/v1_distill_dmd_wan.sh → examples/distill/cli/v1_distill_dmd_wan.sh b/scripts/distill/v1_distill_dmd_wan.sh → examples/distill/cli/v1_distill_dmd_wan.sh
diff --git a/scripts/distill/v1_distill_dmd_wan_VSA.sh → ...les/distill/cli/v1_distill_dmd_wan_VSA.sh b/scripts/distill/v1_distill_dmd_wan_VSA.sh → ...les/distill/cli/v1_distill_dmd_wan_VSA.sh
diff --git a/scripts/huggingface/download_hf.py → examples/huggingface/download_hf.py b/scripts/huggingface/download_hf.py → examples/huggingface/download_hf.py
diff --git a/scripts/huggingface/upload_hf.py → examples/huggingface/upload_hf.py b/scripts/huggingface/upload_hf.py → examples/huggingface/upload_hf.py
diff --git a/...pts/inference/v1_inference_fasthunyuan.sh → ...inference/cli/v1_inference_fasthunyuan.sh b/...pts/inference/v1_inference_fasthunyuan.sh → ...inference/cli/v1_inference_fasthunyuan.sh
diff --git a/scripts/inference/v1_inference_hunyuan.sh → ...les/inference/cli/v1_inference_hunyuan.sh b/scripts/inference/v1_inference_hunyuan.sh → ...les/inference/cli/v1_inference_hunyuan.sh
diff --git a/scripts/inference/v1_inference_longcat.sh → ...les/inference/cli/v1_inference_longcat.sh b/scripts/inference/v1_inference_longcat.sh → ...les/inference/cli/v1_inference_longcat.sh
@@ -5,7 +5,7 @@
 # This script runs LongCat T2V inference using the fastvideo CLI.
 #
 # Usage:
-#   bash scripts/inference/v1_inference_longcat.sh
+#   bash examples/inference/cli/v1_inference_longcat.sh
 #
 # Prerequisites:
 #   - Install fastvideo: pip install -e .
@@ -21,7 +21,7 @@ export MODEL_BASE=FastVideo/LongCat-Video-T2V-Diffusers
 
 # Option 2: Local weights (uncomment if you have local weights)
 # For local weights, convert the official weights to FastVideo native format
-# conversion method: python scripts/checkpoint_conversion/longcat_to_fastvideo.py
+# conversion method: python examples/checkpoint_conversion/longcat_to_fastvideo.py
 # --source /path/to/LongCat-Video/weights/LongCat-Video
 # --output weights/longcat-native
 # export MODEL_BASE=weights/longcat-native

diff --git a/...inference/v1_inference_longcat_distill.sh → ...rence/cli/v1_inference_longcat_distill.sh b/...inference/v1_inference_longcat_distill.sh → ...rence/cli/v1_inference_longcat_distill.sh
@@ -6,7 +6,7 @@
 # Uses the distilled LoRA for faster generation.
 #
 # Usage:
-#   bash scripts/inference/v1_inference_longcat_distill.sh
+#   bash examples/inference/cli/v1_inference_longcat_distill.sh
 #
 # Prerequisites:
 #   - Install fastvideo: pip install -e .

diff --git a/...pts/inference/v1_inference_longcat_i2v.sh → ...inference/cli/v1_inference_longcat_i2v.sh b/...pts/inference/v1_inference_longcat_i2v.sh → ...inference/cli/v1_inference_longcat_i2v.sh
@@ -6,7 +6,7 @@
 # LongCat I2V takes an input image and generates a video from it.
 #
 # Usage:
-#   bash scripts/inference/v1_inference_longcat_i2v.sh
+#   bash examples/inference/cli/v1_inference_longcat_i2v.sh
 #
 # Prerequisites:
 #   - Install fastvideo: pip install -e .

diff --git a/.../v1_inference_longcat_refine_fromvideo.sh → .../v1_inference_longcat_refine_fromvideo.sh b/.../v1_inference_longcat_refine_fromvideo.sh → .../v1_inference_longcat_refine_fromvideo.sh
@@ -6,7 +6,7 @@
 # Run v1_inference_longcat_distill.sh first to generate the 480p video.
 #
 # Usage:
-#   bash scripts/inference/v1_inference_longcat_refine_fromvideo.sh
+#   bash examples/inference/cli/v1_inference_longcat_refine_fromvideo.sh
 #
 # Prerequisites:
 #   - Install fastvideo: pip install -e .

diff --git a/scripts/inference/v1_inference_longcat_vc.sh → .../inference/cli/v1_inference_longcat_vc.sh b/scripts/inference/v1_inference_longcat_vc.sh → .../inference/cli/v1_inference_longcat_vc.sh
@@ -6,7 +6,7 @@
 # LongCat VC takes an input video and generates a continuation of it.
 #
 # Usage:
-#   bash scripts/inference/v1_inference_longcat_vc.sh
+#   bash examples/inference/cli/v1_inference_longcat_vc.sh
 #
 # Prerequisites:
 #   - Install fastvideo: pip install -e .

diff --git a/scripts/inference/v1_inference_wan.sh → examples/inference/cli/v1_inference_wan.sh b/scripts/inference/v1_inference_wan.sh → examples/inference/cli/v1_inference_wan.sh
diff --git a/.../inference/v1_inference_wan_1.3B_VMoba.sh → ...erence/cli/v1_inference_wan_1.3B_VMoba.sh b/.../inference/v1_inference_wan_1.3B_VMoba.sh → ...erence/cli/v1_inference_wan_1.3B_VMoba.sh
diff --git a/scripts/inference/v1_inference_wan_VSA.sh → ...les/inference/cli/v1_inference_wan_VSA.sh b/scripts/inference/v1_inference_wan_VSA.sh → ...les/inference/cli/v1_inference_wan_VSA.sh
diff --git a/...pts/inference/v1_inference_wan_VSA_DMD.sh → ...inference/cli/v1_inference_wan_VSA_DMD.sh b/...pts/inference/v1_inference_wan_VSA_DMD.sh → ...inference/cli/v1_inference_wan_VSA_DMD.sh
diff --git a/scripts/inference/v1_inference_wan_i2v.sh → ...les/inference/cli/v1_inference_wan_i2v.sh b/scripts/inference/v1_inference_wan_i2v.sh → ...les/inference/cli/v1_inference_wan_i2v.sh
diff --git a/scripts/lora_extraction/README.md → examples/lora_extraction/README.md b/scripts/lora_extraction/README.md → examples/lora_extraction/README.md
diff --git a/scripts/lora_extraction/extract_lora.py → examples/lora_extraction/extract_lora.py b/scripts/lora_extraction/extract_lora.py → examples/lora_extraction/extract_lora.py
@@ -1,7 +1,7 @@
 """Extract FastVideo-style LoRA adapters from a fine-tuned model by SVDing (FT - base).
 
 Usage:
-    python scripts/lora_extraction/extract_lora.py \\
+    python examples/lora_extraction/extract_lora.py \\
         --base <base_model> --ft <fine_tuned_model> --out adapter.safetensors --rank 16
 
 Example for models with architectural differences (fallback is automatic):

diff --git a/...a_extraction/lora_inference_comparison.py → ...a_extraction/lora_inference_comparison.py b/...a_extraction/lora_inference_comparison.py → ...a_extraction/lora_inference_comparison.py
diff --git a/scripts/lora_extraction/merge_lora.py → examples/lora_extraction/merge_lora.py b/scripts/lora_extraction/merge_lora.py → examples/lora_extraction/merge_lora.py
diff --git a/scripts/lora_extraction/verify_lora.py → examples/lora_extraction/verify_lora.py b/scripts/lora_extraction/verify_lora.py → examples/lora_extraction/verify_lora.py
diff --git a/...t_preparation/generate_validation_json.py → ...preprocessing/generate_validation_json.py b/...t_preparation/generate_validation_json.py → ...preprocessing/generate_validation_json.py
diff --git a/scripts/preprocess/launch_slurm_text.sh → examples/preprocessing/launch_slurm_text.sh b/scripts/preprocess/launch_slurm_text.sh → examples/preprocessing/launch_slurm_text.sh
@@ -10,12 +10,12 @@ for node_id in {0..7}; do
     start_file=$((node_id * 8 + 1))
 
     echo "Launching text-only node $node_id with files v2m_${start_file}.txt to v2m_$((start_file + 7)).txt"
-    echo "sbatch --job-name=text-${node_id} --output=preprocess_output_text/preprocess-text-node-${node_id}.out --error=preprocess_output_text/preprocess-text-node-${node_id}.err scripts/preprocess/syn_text.slurm $start_file $node_id"
+    echo "sbatch --job-name=text-${node_id} --output=preprocess_output_text/preprocess-text-node-${node_id}.out --error=preprocess_output_text/preprocess-text-node-${node_id}.err examples/preprocessing/syn_text.slurm $start_file $node_id"
 
     sbatch --job-name=text-${node_id} \
            --output=preprocess_output_text/preprocess-text-node-${node_id}.out \
            --error=preprocess_output_text/preprocess-text-node-${node_id}.err \
-           scripts/preprocess/syn_text.slurm $start_file $node_id
+           examples/preprocessing/syn_text.slurm $start_file $node_id
 done
 
 echo "All 8 text-only nodes launched successfully!" 
diff --git a/.../dataset_preparation/prepare_json_file.py → examples/preprocessing/prepare_json_file.py b/.../dataset_preparation/prepare_json_file.py → examples/preprocessing/prepare_json_file.py
diff --git a/scripts/dataset_preparation/resize_videos.py → examples/preprocessing/resize_videos.py b/scripts/dataset_preparation/resize_videos.py → examples/preprocessing/resize_videos.py
diff --git a/scripts/preprocess/syn_text.slurm → examples/preprocessing/syn_text.slurm b/scripts/preprocess/syn_text.slurm → examples/preprocessing/syn_text.slurm
diff --git a/.../preprocess/v1_preprocess_wan_data_i2v.sh → ...eprocessing/v1_preprocess_wan_data_i2v.sh b/.../preprocess/v1_preprocess_wan_data_i2v.sh → ...eprocessing/v1_preprocess_wan_data_i2v.sh
diff --git a/.../preprocess/v1_preprocess_wan_data_t2v.sh → ...eprocessing/v1_preprocess_wan_data_t2v.sh b/.../preprocess/v1_preprocess_wan_data_t2v.sh → ...eprocessing/v1_preprocess_wan_data_t2v.sh
diff --git a/examples/training/finetune/Wan2.1-Fun-1.3B-InP/crush_smol/download_dataset.sh b/examples/training/finetune/Wan2.1-Fun-1.3B-InP/crush_smol/download_dataset.sh
@@ -1,3 +1,3 @@
 #!/bin/bash
 
-python scripts/huggingface/download_hf.py --repo_id "wlsaidhi/crush-smol-merged" --local_dir "data/crush-smol" --repo_type "dataset"
+python examples/huggingface/download_hf.py --repo_id "wlsaidhi/crush-smol-merged" --local_dir "data/crush-smol" --repo_type "dataset"
diff --git a/examples/training/finetune/Wan2.1-VSA/Wan-Syn-Data/download_dataset.sh b/examples/training/finetune/Wan2.1-VSA/Wan-Syn-Data/download_dataset.sh
@@ -3,6 +3,6 @@
 
 
 # 480P dataset
-python scripts/huggingface/download_hf.py --repo_id "FastVideo/Wan-Syn_77x448x832_600k" --local_dir "data/Wan-Syn_77x448x832_600k" --repo_type "dataset"
+python examples/huggingface/download_hf.py --repo_id "FastVideo/Wan-Syn_77x448x832_600k" --local_dir "data/Wan-Syn_77x448x832_600k" --repo_type "dataset"
 # 720P dataset
-python scripts/huggingface/download_hf.py --repo_id "FastVideo/Wan-Syn_77x768x1280_250k" --local_dir "data/Wan-Syn_77x768x1280_250k" --repo_type "dataset"
+python examples/huggingface/download_hf.py --repo_id "FastVideo/Wan-Syn_77x768x1280_250k" --local_dir "data/Wan-Syn_77x768x1280_250k" --repo_type "dataset"
diff --git a/scripts/finetune/finetune_v1.sh → ...ples/training/finetune/cli/finetune_v1.sh b/scripts/finetune/finetune_v1.sh → ...ples/training/finetune/cli/finetune_v1.sh
diff --git a/examples/training/finetune/wan_i2v_14B_480p/crush_smol/download_dataset.sh b/examples/training/finetune/wan_i2v_14B_480p/crush_smol/download_dataset.sh
@@ -1,3 +1,3 @@
 #!/bin/bash
 
-python scripts/huggingface/download_hf.py --repo_id "wlsaidhi/crush-smol-merged" --local_dir "data/crush-smol" --repo_type "dataset"
+python examples/huggingface/download_hf.py --repo_id "wlsaidhi/crush-smol-merged" --local_dir "data/crush-smol" --repo_type "dataset"
diff --git a/examples/training/finetune/wan_t2v_1.3B/crush_smol/download_dataset.sh b/examples/training/finetune/wan_t2v_1.3B/crush_smol/download_dataset.sh
@@ -1,3 +1,3 @@
 #!/bin/bash
 
-python scripts/huggingface/download_hf.py --repo_id "wlsaidhi/crush-smol-merged" --local_dir "data/crush-smol" --repo_type "dataset"
+python examples/huggingface/download_hf.py --repo_id "wlsaidhi/crush-smol-merged" --local_dir "data/crush-smol" --repo_type "dataset"
diff --git a/fastvideo/tests/lora_extraction/test_lora_extraction.py b/fastvideo/tests/lora_extraction/test_lora_extraction.py
@@ -2,9 +2,9 @@
 import sys
 from pathlib import Path
 
-# Add scripts/lora_extraction to path for imports
+# Add examples/lora_extraction to path for imports
 repo_root = Path(__file__).parents[3]
-lora_scripts = repo_root / "scripts" / "lora_extraction"
+lora_scripts = repo_root / "examples" / "lora_extraction"
 sys.path.insert(0, str(lora_scripts))
 
 # Import the core functions