Download command.sh from edessa/EMG: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/datasets/edessa/EMG/resolve/main/command.sh
- Command line
-
hf download hf://datasets/edessa/EMG/command.sh
-
curl -L -o command.sh https://huggingface.co/datasets/edessa/EMG/resolve/main/command.sh
5.3 kB
| nautilus sftp://edessale@nexuscfar00.umiacs.umd.edu/fs/vulcan-projects/Force_Learning | |
| /fs/vulcan-projects/Force_Learning/EMG_Learning/VideoX-Fun/models/Wan2.1-Fun-V1.1-1.3B-Control-Camera | |
| https://huggingface.co/alibaba-pai/Wan2.2-Fun-5B-Control | |
| https://huggingface.co/alibaba-pai/Wan2.1-Fun-V1.1-1.3B-Control-Camera | |
| export DATASET_NAME="" | |
| export DATASET_META_NAME="/fs/vulcan-projects/Force_Learning/EMG/videoxfun_metadata.json" | |
| export MODEL_NAME="/fs/vulcan-projects/Force_Learning/EMG_Learning/VideoX-Fun/models/Wan2.1-Fun-V1.1-1.3B-Control-Camera" | |
| export MODEL_NAME="/fs/vulcan-projects/Force_Learning/EMG_Learning/VideoX-Fun/models/Wan2.2-Fun-5B-Control" | |
| export DATASET_NAME="" | |
| export DATASET_META_NAME="/fs/vulcan-projects/Force_Learning/EMG/videoxfun_metadata.json" | |
| accelerate launch --mixed_precision="bf16" scripts/wan2.2_fun/train_control.py \ | |
| --config_path="config/wan2.2/wan_civitai_5b.yaml" \ | |
| --pretrained_model_name_or_path=$MODEL_NAME \ | |
| --train_data_dir=$DATASET_NAME \ | |
| --train_data_meta=$DATASET_META_NAME \ | |
| --image_sample_size=640 \ | |
| --video_sample_size=640 \ | |
| --token_sample_size=640 \ | |
| --video_sample_stride=1 \ | |
| --video_sample_n_frames=49 \ | |
| --train_batch_size=1 \ | |
| --video_repeat=1 \ | |
| --gradient_accumulation_steps=1 \ | |
| --dataloader_num_workers=2 \ | |
| --num_train_epochs=100 \ | |
| --checkpointing_steps=200 \ | |
| --learning_rate=2e-05 \ | |
| --lr_scheduler="constant_with_warmup" \ | |
| --lr_warmup_steps=100 \ | |
| --seed=42 \ | |
| --output_dir="output_dir" \ | |
| --gradient_checkpointing \ | |
| --mixed_precision="bf16" \ | |
| --adam_weight_decay=3e-2 \ | |
| --adam_epsilon=1e-10 \ | |
| --vae_mini_batch=1 \ | |
| --max_grad_norm=0.05 \ | |
| --random_hw_adapt \ | |
| --control_signal_mode emg \ | |
| --training_with_video_token_length \ | |
| --uniform_sampling \ | |
| --boundary_type="full" \ | |
| --train_mode="control_ref" \ | |
| --control_ref_image="first_frame" \ | |
| --add_inpaint_info \ | |
| --add_full_ref_image_in_self_attention \ | |
| --trainable_modules "." | |
| accelerate launch --mixed_precision="bf16" scripts/wan2.1_fun/train_control.py \ | |
| --config_path="config/wan2.1/wan_civitai.yaml" \ | |
| --pretrained_model_name_or_path=$MODEL_NAME \ | |
| --train_data_dir=$DATASET_NAME \ | |
| --train_data_meta=$DATASET_META_NAME \ | |
| --image_sample_size=640 \ | |
| --video_sample_size=640 \ | |
| --token_sample_size=640 \ | |
| --video_sample_stride=1 \ | |
| --video_sample_n_frames=49 \ | |
| --train_batch_size=1 \ | |
| --video_repeat=1 \ | |
| --gradient_accumulation_steps=1 \ | |
| --dataloader_num_workers=2 \ | |
| --num_train_epochs=100 \ | |
| --checkpointing_steps=200 \ | |
| --learning_rate=2e-05 \ | |
| --lr_scheduler="constant_with_warmup" \ | |
| --lr_warmup_steps=100 \ | |
| --seed=42 \ | |
| --output_dir="output_dir" \ | |
| --gradient_checkpointing \ | |
| --mixed_precision="bf16" \ | |
| --adam_weight_decay=3e-2 \ | |
| --adam_epsilon=1e-10 \ | |
| --vae_mini_batch=1 \ | |
| --max_grad_norm=0.05 \ | |
| --random_hw_adapt \ | |
| --training_with_video_token_length \ | |
| --uniform_sampling \ | |
| --train_mode="control_ref" \ | |
| --control_ref_image="random" \ | |
| --add_full_ref_image_in_self_attention \ | |
| --trainable_modules "." \ | |
| --profile_timings_every=100 \ | |
| --validation_num_samples 200 \ | |
| --validation_steps 3 \ | |
| --resume_from_checkpoint "/fs/vulcan-projects/Force_Learning/EMG_Learning/VideoX-Fun/output_dir/checkpoint-2800" | |
| cd /fs/vulcan-projects/Force_Learning/EMG_Learning/VideoX-Fun | |
| python3 scripts/wan2.1_fun/generate_emg_dataset_wan.py \ | |
| --config_path config/wan2.1/wan_civitai.yaml \ | |
| --pretrained_model_name_or_path "$MODEL_NAME" \ | |
| --transformer_path /fs/vulcan-projects/Force_Learning/EMG_Learning/VideoX-Fun/output_dir/checkpoint-2800 \ | |
| --train_data_dir "$DATASET_NAME" \ | |
| --train_data_meta "$DATASET_META_NAME" \ | |
| --image_sample_size 640 \ | |
| --video_sample_size 640 \ | |
| --video_sample_stride 1 \ | |
| --video_sample_n_frames 49 \ | |
| --train_mode "control_ref" \ | |
| --add_full_ref_image_in_self_attention \ | |
| --n_samples 8 \ | |
| --output_dir output_dir/emg_generations | |
| export DATASET_NAME="" | |
| export DATASET_META_NAME="/fs/vulcan-projects/Force_Learning/EMG/videoxfun_metadata.json" | |
| export MODEL_NAME="/fs/vulcan-projects/Force_Learning/EMG_Learning/VideoX-Fun/models/Wan2.1-Fun-V1.1-1.3B-Control-Camera" | |
| accelerate launch --mixed_precision="bf16" scripts/wan2.1_fun/train_control_lora.py \ | |
| --config_path="config/wan2.1/wan_civitai.yaml" \ | |
| --pretrained_model_name_or_path=$MODEL_NAME \ | |
| --train_data_dir=$DATASET_NAME \ | |
| --train_data_meta=$DATASET_META_NAME \ | |
| --image_sample_size=640 \ | |
| --video_sample_size=640 \ | |
| --token_sample_size=640 \ | |
| --video_sample_stride=1 \ | |
| --video_sample_n_frames=49 \ | |
| --train_batch_size=4 \ | |
| --video_repeat=1 \ | |
| --gradient_accumulation_steps=1 \ | |
| --dataloader_num_workers=2 \ | |
| --num_train_epochs=100 \ | |
| --checkpointing_steps=200 \ | |
| --learning_rate=1e-04 \ | |
| --seed=42 \ | |
| --output_dir="output_dir" \ | |
| --gradient_checkpointing \ | |
| --mixed_precision="bf16" \ | |
| --adam_weight_decay=3e-2 \ | |
| --adam_epsilon=1e-10 \ | |
| --vae_mini_batch=1 \ | |
| --max_grad_norm=0.05 \ | |
| --random_hw_adapt \ | |
| --training_with_video_token_length \ | |
| --uniform_sampling \ | |
| --train_mode="control_ref" \ | |
| --control_ref_image="random" \ | |
| --add_full_ref_image_in_self_attention \ | |
| --rank=64 \ | |
| --network_alpha=32 \ | |
| --target_name="q,k,v,ffn.0,ffn.2" \ | |
| --use_peft_lora \ | |
| --profile_timings_every=100 | |