YFanwang commited on
Commit
e858895
·
verified ·
1 Parent(s): 85ff4ea

Upload VideoX-Fun/config

Browse files
VideoX-Fun/config/wan2.1/wan_civitai.yaml ADDED
@@ -0,0 +1,39 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format: civitai
2
+ pipeline: Wan
3
+ transformer_additional_kwargs:
4
+ transformer_subpath: ./
5
+ dict_mapping:
6
+ in_dim: in_channels
7
+ dim: hidden_size
8
+
9
+ vae_kwargs:
10
+ vae_subpath: Wan2.1_VAE.pth
11
+ temporal_compression_ratio: 4
12
+ spatial_compression_ratio: 8
13
+
14
+ text_encoder_kwargs:
15
+ text_encoder_subpath: models_t5_umt5-xxl-enc-bf16.pth
16
+ tokenizer_subpath: google/umt5-xxl
17
+ text_length: 512
18
+ vocab: 256384
19
+ dim: 4096
20
+ dim_attn: 4096
21
+ dim_ffn: 10240
22
+ num_heads: 64
23
+ num_layers: 24
24
+ num_buckets: 32
25
+ shared_pos: False
26
+ dropout: 0.0
27
+
28
+ scheduler_kwargs:
29
+ scheduler_subpath: null
30
+ num_train_timesteps: 1000
31
+ shift: 5.0
32
+ use_dynamic_shifting: false
33
+ base_shift: 0.5
34
+ max_shift: 1.15
35
+ base_image_seq_len: 256
36
+ max_image_seq_len: 4096
37
+
38
+ image_encoder_kwargs:
39
+ image_encoder_subpath: models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
VideoX-Fun/config/wan2.1/wan_civitai_sd.yaml ADDED
@@ -0,0 +1,39 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format: civitai
2
+ pipeline: Wan
3
+ transformer_additional_kwargs:
4
+ transformer_subpath: ./
5
+ dict_mapping:
6
+ in_dim: in_channels
7
+ dim: hidden_size
8
+
9
+ vae_kwargs:
10
+ vae_subpath: Wan2.1_VAE.pth
11
+ temporal_compression_ratio: 4
12
+ spatial_compression_ratio: 8
13
+
14
+ text_encoder_kwargs:
15
+ text_encoder_subpath: models_t5_umt5-xxl-enc-bf16.pth
16
+ tokenizer_subpath: google/umt5-xxl
17
+ text_length: 512
18
+ vocab: 256384
19
+ dim: 4096
20
+ dim_attn: 4096
21
+ dim_ffn: 10240
22
+ num_heads: 64
23
+ num_layers: 24
24
+ num_buckets: 32
25
+ shared_pos: False
26
+ dropout: 0.0
27
+
28
+ scheduler_kwargs:
29
+ # scheduler_subpath: null
30
+ # num_train_timesteps: 1000
31
+ shift: 5.0
32
+ # use_dynamic_shifting: false
33
+ # base_shift: 0.5
34
+ # max_shift: 1.15
35
+ # base_image_seq_len: 256
36
+ # max_image_seq_len: 4096
37
+
38
+ image_encoder_kwargs:
39
+ image_encoder_subpath: models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
VideoX-Fun/config/wan2.2/wan_civitai_5b.yaml ADDED
@@ -0,0 +1,41 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format: civitai
2
+ pipeline: Wan
3
+ transformer_additional_kwargs:
4
+ transformer_low_noise_model_subpath: ./
5
+ transformer_combination_type: "single"
6
+ dict_mapping:
7
+ in_dim: in_channels
8
+ dim: hidden_size
9
+
10
+ vae_kwargs:
11
+ vae_type: "AutoencoderKLWan3_8"
12
+ vae_subpath: Wan2.2_VAE.pth
13
+ temporal_compression_ratio: 4
14
+ spatial_compression_ratio: 16
15
+
16
+ text_encoder_kwargs:
17
+ text_encoder_subpath: models_t5_umt5-xxl-enc-bf16.pth
18
+ tokenizer_subpath: google/umt5-xxl
19
+ text_length: 512
20
+ vocab: 256384
21
+ dim: 4096
22
+ dim_attn: 4096
23
+ dim_ffn: 10240
24
+ num_heads: 64
25
+ num_layers: 24
26
+ num_buckets: 32
27
+ shared_pos: False
28
+ dropout: 0.0
29
+
30
+ scheduler_kwargs:
31
+ scheduler_subpath: null
32
+ num_train_timesteps: 1000
33
+ shift: 12.0
34
+ use_dynamic_shifting: false
35
+ base_shift: 0.5
36
+ max_shift: 1.15
37
+ base_image_seq_len: 256
38
+ max_image_seq_len: 4096
39
+
40
+ image_encoder_kwargs:
41
+ image_encoder_subpath: models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
VideoX-Fun/config/wan2.2/wan_civitai_i2v.yaml ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format: civitai
2
+ pipeline: Wan
3
+ transformer_additional_kwargs:
4
+ transformer_low_noise_model_subpath: ./low_noise_model
5
+ transformer_high_noise_model_subpath: ./high_noise_model
6
+ transformer_combination_type: "moe"
7
+ boundary: 0.900
8
+ dict_mapping:
9
+ in_dim: in_channels
10
+ dim: hidden_size
11
+
12
+ vae_kwargs:
13
+ vae_type: "AutoencoderKLWan"
14
+ vae_subpath: Wan2.1_VAE.pth
15
+ temporal_compression_ratio: 4
16
+ spatial_compression_ratio: 8
17
+
18
+ text_encoder_kwargs:
19
+ text_encoder_subpath: models_t5_umt5-xxl-enc-bf16.pth
20
+ tokenizer_subpath: google/umt5-xxl
21
+ text_length: 512
22
+ vocab: 256384
23
+ dim: 4096
24
+ dim_attn: 4096
25
+ dim_ffn: 10240
26
+ num_heads: 64
27
+ num_layers: 24
28
+ num_buckets: 32
29
+ shared_pos: False
30
+ dropout: 0.0
31
+
32
+ scheduler_kwargs:
33
+ scheduler_subpath: null
34
+ num_train_timesteps: 1000
35
+ shift: 5.0
36
+ use_dynamic_shifting: false
37
+ base_shift: 0.5
38
+ max_shift: 1.15
39
+ base_image_seq_len: 256
40
+ max_image_seq_len: 4096
41
+
42
+ image_encoder_kwargs:
43
+ image_encoder_subpath: models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
VideoX-Fun/config/wan2.2/wan_civitai_t2v.yaml ADDED
@@ -0,0 +1,43 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ format: civitai
2
+ pipeline: Wan
3
+ transformer_additional_kwargs:
4
+ transformer_low_noise_model_subpath: ./low_noise_model
5
+ transformer_high_noise_model_subpath: ./high_noise_model
6
+ transformer_combination_type: "moe"
7
+ boundary: 0.875
8
+ dict_mapping:
9
+ in_dim: in_channels
10
+ dim: hidden_size
11
+
12
+ vae_kwargs:
13
+ vae_type: "AutoencoderKLWan"
14
+ vae_subpath: Wan2.1_VAE.pth
15
+ temporal_compression_ratio: 4
16
+ spatial_compression_ratio: 8
17
+
18
+ text_encoder_kwargs:
19
+ text_encoder_subpath: models_t5_umt5-xxl-enc-bf16.pth
20
+ tokenizer_subpath: google/umt5-xxl
21
+ text_length: 512
22
+ vocab: 256384
23
+ dim: 4096
24
+ dim_attn: 4096
25
+ dim_ffn: 10240
26
+ num_heads: 64
27
+ num_layers: 24
28
+ num_buckets: 32
29
+ shared_pos: False
30
+ dropout: 0.0
31
+
32
+ scheduler_kwargs:
33
+ scheduler_subpath: null
34
+ num_train_timesteps: 1000
35
+ shift: 12.0
36
+ use_dynamic_shifting: false
37
+ base_shift: 0.5
38
+ max_shift: 1.15
39
+ base_image_seq_len: 256
40
+ max_image_seq_len: 4096
41
+
42
+ image_encoder_kwargs:
43
+ image_encoder_subpath: models_clip_open-clip-xlm-roberta-large-vit-huge-14.pth
VideoX-Fun/config/zero_stage2_config.json ADDED
@@ -0,0 +1,16 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bf16": {
3
+ "enabled": true
4
+ },
5
+ "train_micro_batch_size_per_gpu": 1,
6
+ "train_batch_size": "auto",
7
+ "gradient_accumulation_steps": "auto",
8
+ "dump_state": true,
9
+ "zero_optimization": {
10
+ "stage": 2,
11
+ "overlap_comm": true,
12
+ "contiguous_gradients": true,
13
+ "sub_group_size": 1e9,
14
+ "reduce_bucket_size": 5e8
15
+ }
16
+ }
VideoX-Fun/config/zero_stage3_config.json ADDED
@@ -0,0 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bf16": {
3
+ "enabled": true
4
+ },
5
+ "train_micro_batch_size_per_gpu": 1,
6
+ "train_batch_size": "auto",
7
+ "gradient_accumulation_steps": "auto",
8
+ "gradient_clipping": "auto",
9
+ "steps_per_print": 2000,
10
+ "wall_clock_breakdown": false,
11
+ "zero_optimization": {
12
+ "stage": 3,
13
+ "overlap_comm": true,
14
+ "contiguous_gradients": true,
15
+ "reduce_bucket_size": 5e8,
16
+ "sub_group_size": 1e9,
17
+ "stage3_max_live_parameters": 1e9,
18
+ "stage3_max_reuse_distance": 1e9,
19
+ "stage3_gather_16bit_weights_on_model_save": "auto",
20
+ "offload_optimizer": {
21
+ "device": "none"
22
+ },
23
+ "offload_param": {
24
+ "device": "none"
25
+ }
26
+ }
27
+ }
28
+
VideoX-Fun/config/zero_stage3_config_cpu_offload.json ADDED
@@ -0,0 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "bf16": {
3
+ "enabled": true
4
+ },
5
+ "train_micro_batch_size_per_gpu": 1,
6
+ "train_batch_size": "auto",
7
+ "gradient_accumulation_steps": "auto",
8
+ "gradient_clipping": "auto",
9
+ "steps_per_print": 2000,
10
+ "wall_clock_breakdown": false,
11
+ "zero_optimization": {
12
+ "stage": 3,
13
+ "overlap_comm": true,
14
+ "contiguous_gradients": true,
15
+ "reduce_bucket_size": 5e8,
16
+ "sub_group_size": 1e9,
17
+ "stage3_max_live_parameters": 1e9,
18
+ "stage3_max_reuse_distance": 1e9,
19
+ "stage3_gather_16bit_weights_on_model_save": "auto",
20
+ "offload_optimizer": {
21
+ "device": "cpu"
22
+ },
23
+ "offload_param": {
24
+ "device": "cpu"
25
+ }
26
+ }
27
+ }
28
+