I found 2 WF that i liked and decide to put them together:
I dont know what settings is right to use (cfg/steps/ lora strength). But it seems to be working as it is for now.
I use Sage Attention - LINK
UPDATE COMFYUI BEFORE USE
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v.1.0 (WAN 2.2 FLF2V)
WAN 2.2 has FLF2V (First-Last Frame to Video) native capabilities. So i tried to adjust my workflow to make it work and seems it does. Hope you like it.
Enjoy.
==========
v.1.0 (WAN 2.2 I2V)
I just rearange nodes so it works with WAN 2.2 GGUF
https://huggingface.co/bullerwins/Wan2.2-I2V-A14B-GGUF/tree/main
Notice that for 14B model you need both models - HIGH noise and LOW noise
==========
v.1.1 (WAN 2.1 I2V)
Instead using CausVid lora i used FusionX lora which is already have CausVid
I set lora streinght 0.4 in first Ksampler (HIGH CFG START) and 0.8 in second one (LOW CFG END)
In version 1.0 you can just change loras in Dual samplers group
==========
v.1.0 (WAN 2.1 I2V)
1 - CausVid 2 Sampler Workflow for Wan 480p/720p I2V (Main part)
I Used this lora: Wan21_CausVid_14B_T2V_lora_rank32.safetensors
2 - WAN 2.1 IMAGE to VIDEO with Caption and Postprocessing (Florence Caption, last frame, Color match)
==========
I saw suggestions that dpmpp_2m - normal works good.
There is dpmpp_2m - simple in this WF
Description
Instead Caus i use FusionX lora
FAQ
Comments (35)
With accelerators, CFG needs to be 1, LoRAs usually need to be higher than usual, and steps will be between 6 and 10 usually. Taking CFG above 1 usually doubles render time. Again too many steps and the advantage of accelerating methods is reduced.
PS accelerators ruin prompt adherence, but that goes with the territory. One must experiment to find which types of prompt are still followed. BUT controlnets can mitigate this issue by bringing motion from an existing video.
Thnx, i just like the result of this WF. No pixelization, no random contrast/brightness jumps. It take ~15 min to render with 20 steps on 3080 Ti. I use Sage . I didnt add TeaCache in it. I think it lower hands quality. But i'm still trying things.
KSamplerAdvanced
mat1 and mat2 shapes cannot be multiplied (231x768 and 4096x5120)
may i know how to fix it?
@satangel Hello. I didn't have that issue yet. But i found some toppics on reddit they say it may cause by lora or other models that not comatible. Do you use any lora besides FusionX? Or you changed some other models in WF? Its hard to say cus your screen not showing what you have in nodes.
got prompt
Using xformers attention in VAE
Using xformers attention in VAE
VAE load device: cuda:0, offload device: cpu, dtype: torch.bfloat16
Requested to load CLIPVisionModelProjection
loaded completely 9.5367431640625e+25 1208.09814453125 True
Requested to load SD1ClipModel
loaded completely 9.5367431640625e+25 235.84423828125 True
CLIP/text encoder model load device: cpu, offload device: cpu, current: cpu, dtype: torch.float16
clip missing: ['text_model.embeddings.token_embedding.weight', 'text_model.embeddings.position_embedding.weight', 'text_model.encoder.layers.0.layer_norm1.weight', 'text_model.encoder.layers.0.layer_norm1.bias', 'text_model.encoder.layers.0.self_attn.q_proj.weight', 'text_model.encoder.layers.0.self_attn.q_proj.bias', 'text_model.encoder.layers.0.self_attn.k_proj.weight', 'text_model.encoder.layers.0.self_attn.k_proj.bias', 'text_model.encoder.layers.0.self_attn.v_proj.weight', 'text_model.encoder.layers.0.self_attn.v_proj.bias', 'text_model.encoder.layers.0.self_attn.out_proj.weight', 'text_model.encoder.layers.0.self_attn.out_proj.bias', 'text_model.encoder.layers.0.layer_norm2.weight', 'text_model.encoder.layers.0.layer_norm2.bias', 'text_model.encoder.layers.0.mlp.fc1.weight', 'text_model.encoder.layers.0.mlp.fc1.bias', 'text_model.encoder.layers.0.mlp.fc2.weight', 'text_model.encoder.layers.0.mlp.fc2.bias', 'text_model.encoder.layers.1.layer_norm1.weight', 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gguf qtypes: F16 (693), Q3_K (489), F32 (149)
model weight dtype torch.float16, manual cast: None
model_type FLOW
[DisTorch] Full allocation string: #cuda:0;24.0;cpu
Token indices sequence length is longer than the specified maximum sequence length for this model (333 > 77). Running this sequence through the model will result in indexing errors
Requested to load WanVAE
loaded completely 2658.0 242.02829551696777 True
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Requested to load WAN21_Vace
0 models unloaded.
loaded partially 128.0 127.9981689453125 0
===============================================
DisTorch Virtual VRAM Analysis
===============================================
Object Role Original(GB) Total(GB) Virt(GB)
-----------------------------------------------
cuda:0 recip 8.00GB 32.00GB +24.00GB
cpu donor 63.84GB 39.84GB -24.00GB
-----------------------------------------------
model model 7.29GB 0.00GB -24.00GB
Warning: Model size is greater than 90% of recipient VRAM. 0.09 GB of GGML Layers Offloaded Automatically to Virtual VRAM.
Allocation String cuda:0,0.0000;cpu,0.3759
===============================================
DisTorch Device Allocations
===============================================
Device Alloc % Total (GB) Alloc (GB)
-----------------------------------------------
cuda:0 0% 8.00 0.00
cpu 37% 63.84 24.00
-----------------------------------------------
DisTorch GGML Layer Distribution
-----------------------------------------------
Layer Type Layers Memory (MB) % Total
-----------------------------------------------
Conv3d 2 8.79 0.1%
Linear 495 7455.85 99.8%
LayerNorm 145 0.94 0.0%
RMSNorm 192 1.88 0.0%
-----------------------------------------------
DisTorch Final Device/Layer Assignments
-----------------------------------------------
Device Layers Memory (MB) % Total
-----------------------------------------------
cuda:0 0 0.00 0.0%
cpu 834 7467.45 100.0%
-----------------------------------------------
0%| | 0/4 [00:00<?, ?it/s]
!!! Exception during processing !!! mat1 and mat2 shapes cannot be multiplied (154x768 and 4096x5120)
Traceback (most recent call last):
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\execution.py", line 361, in execute
output_data, output_ui, has_subgraph = get_output_data(obj, input_data_all, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\execution.py", line 236, in get_output_data
return_values = mapnode_over_list(obj, input_data_all, obj.FUNCTION, allow_interrupt=True, execution_block_cb=execution_block_cb, pre_execute_cb=pre_execute_cb)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\execution.py", line 208, in mapnode_over_list
process_inputs(input_dict, i)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\execution.py", line 197, in process_inputs
results.append(getattr(obj, func)(**inputs))
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\nodes.py", line 1550, in sample
return common_ksampler(model, noise_seed, steps, cfg, sampler_name, scheduler, positive, negative, latent_image, denoise=denoise, disable_noise=disable_noise, start_step=start_at_step, last_step=end_at_step, force_full_denoise=force_full_denoise)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\nodes.py", line 1483, in common_ksampler
samples = comfy.sample.sample(model, noise, steps, cfg, sampler_name, scheduler, positive, negative, latent_image,
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\comfy\sample.py", line 45, in sample
samples = sampler.sample(noise, positive, negative, cfg=cfg, latent_image=latent_image, start_step=start_step, last_step=last_step, force_full_denoise=force_full_denoise, denoise_mask=noise_mask, sigmas=sigmas, callback=callback, disable_pbar=disable_pbar, seed=seed)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\comfy\samplers.py", line 1139, in sample
return sample(self.model, noise, positive, negative, cfg, self.device, sampler, sigmas, self.model_options, latent_image=latent_image, denoise_mask=denoise_mask, callback=callback, disable_pbar=disable_pbar, seed=seed)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\comfy\samplers.py", line 1029, in sample
return cfg_guider.sample(noise, latent_image, sampler, sigmas, denoise_mask, callback, disable_pbar, seed)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\comfy\samplers.py", line 1014, in sample
output = executor.execute(noise, latent_image, sampler, sigmas, denoise_mask, callback, disable_pbar, seed)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\comfy\patcher_extension.py", line 111, in execute
return self.original(*args, **kwargs)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\comfy\samplers.py", line 982, in outer_sample
output = self.inner_sample(noise, latent_image, device, sampler, sigmas, denoise_mask, callback, disable_pbar, seed)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\comfy\samplers.py", line 965, in inner_sample
samples = executor.execute(self, sigmas, extra_args, callback, noise, latent_image, denoise_mask, disable_pbar)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\comfy\patcher_extension.py", line 111, in execute
return self.original(*args, **kwargs)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\comfy\samplers.py", line 744, in sample
samples = self.sampler_function(model_k, noise, sigmas, extra_args=extra_args, callback=k_callback, disable=disable_pbar, **self.extra_options)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\Python\lib\site-packages\torch\utils\_contextlib.py", line 116, in decorate_context
return func(*args, **kwargs)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\comfy\k_diffusion\sampling.py", line 741, in sample_dpmpp_2m
denoised = model(x, sigmas[i] s_in, *extra_args)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\comfy\samplers.py", line 396, in call
out = self.inner_model(x, sigma, model_options=model_options, seed=seed)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\comfy\samplers.py", line 945, in call
return self.predict_noise(*args, **kwargs)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\comfy\samplers.py", line 948, in predict_noise
return sampling_function(self.inner_model, x, timestep, self.conds.get("negative", None), self.conds.get("positive", None), self.cfg, model_options=model_options, seed=seed)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\comfy\samplers.py", line 376, in sampling_function
out = calc_cond_batch(model, conds, x, timestep, model_options)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\comfy\samplers.py", line 206, in calc_cond_batch
return executor.execute(model, conds, x_in, timestep, model_options)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\comfy\patcher_extension.py", line 111, in execute
return self.original(*args, **kwargs)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\comfy\samplers.py", line 325, in calccond_batch
output = model.apply_model(input_x, timestep_, **c).chunk(batch_chunks)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\comfy\model_base.py", line 151, in apply_model
return comfy.patcher_extension.WrapperExecutor.new_class_executor(
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\comfy\patcher_extension.py", line 111, in execute
return self.original(*args, **kwargs)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\comfy\model_base.py", line 189, in applymodel
model_output = self.diffusion_model(xc, t, context=context, control=control, transformer_options=transformer_options, **extra_conds).float()
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\Python\lib\site-packages\torch\nn\modules\module.py", line 1751, in wrappedcall_impl
return self._call_impl(*args, **kwargs)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\Python\lib\site-packages\torch\nn\modules\module.py", line 1762, in callimpl
return forward_call(*args, **kwargs)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\comfy\ldm\wan\model.py", line 563, in forward
return self.forward_orig(x, timestep, context, clip_fea=clip_fea, freqs=freqs, transformer_options=transformer_options, **kwargs)[:, :, :t, :h, :w]
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\comfy\ldm\wan\model.py", line 662, in forward_orig
context = self.text_embedding(context)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\Python\lib\site-packages\torch\nn\modules\module.py", line 1751, in wrappedcall_impl
return self._call_impl(*args, **kwargs)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\Python\lib\site-packages\torch\nn\modules\module.py", line 1762, in callimpl
return forward_call(*args, **kwargs)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\Python\lib\site-packages\torch\nn\modules\container.py", line 240, in forward
input = module(input)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\Python\lib\site-packages\torch\nn\modules\module.py", line 1751, in wrappedcall_impl
return self._call_impl(*args, **kwargs)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\Python\lib\site-packages\torch\nn\modules\module.py", line 1762, in callimpl
return forward_call(*args, **kwargs)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\comfy\ops.py", line 84, in forward
return self.forward_comfy_cast_weights(*args, **kwargs)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\custom_nodes\ComfyUI-GGUF\ops.py", line 217, in forward_comfy_cast_weights
out = super().forward_comfy_cast_weights(input, args, *kwargs)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\ComfyUI\comfy\ops.py", line 80, in forward_comfy_cast_weights
return torch.nn.functional.linear(input, weight, bias)
File "D:\AI-T8-video-onekey-20250615\AI-T8-video-onekey-20250615\Python\lib\site-packages\torch\_tensor.py", line 1668, in __torch_function__
ret = func(*args, **kwargs)
RuntimeError: mat1 and mat2 shapes cannot be multiplied (154x768 and 4096x5120)
Prompt executed in 47.90 seconds
@satangel I reproduced your error. The issiue is the CLIP.
Try to use umt5_xxl_fp8_e4m3fn_scaled.safetensors instead of umt5-xxl-enc-fp8_e4m3fn.safetensors
https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/tree/main/split_files/text_encoders
@GFrost Many Thanks, it finally working now after i change the scaled model.
Checked this and the results were very impressive. I used "switch to own prompt =TRUE" though, results were very random sometimes with it off.
Thnx, glad you liked it.
Yeah it meant to be helper. I do use own prompt sometimes with slightly edit of autogenerated one.
You can also use lesser florence model. it will describe small portion of the picture so you can add more later.
Does Results were random even if you add "After text" or/and "Pre text" ?
@GFrost I'd have to try that too and see what happens.
@GFrost You're right, the first time i added my prompt in "my own prompt" and the results were random, adding it to pre text created a great prompt with just "girl is talking on smartphone", sorry for that, i'm not used to Florence, you learn something new every day lol
@skyrimer3d True. I found florence in one of the WF lately and using it ever since.
Have fun =)
https://ibb.co/pvqYrYSz
[url=https://ibb.co/pvqYrYSz][img]https://i.ibb.co/pvqYrYSz/image-4.png[/img][/url]
how come after interpolate the video quality seems become less in quality like the colour fading? is it anyway to improve it? is it suppose to upscale first or what?
![https://ibb.co/pvqYrYSz][img]https://i.ibb.co/pvqYrYSz/image-4.png[/img][/url]](https://ibb.co/pvqYrYSz][img]https://i.ibb.co/pvqYrYSz/image-4.png[/img][/url]){kind=link}
I've checked all wfs i can find on civitai, even the latest ones with self forcing etc, nothing beats the amazing results and color matching of your wf (what is the fuss with self forcing, motion is terrible over 5 sec), congrats! I wanted to ask, ccan you make a wf based on this with first frame and last frame? I don't have a lot of buzz but i can send some.
Thanks. I Just combine 2 WF together basicly =) and its first one. Im not a great builder of WF but i will see what i can do in spare time.
P.S. Do not Buzz in advance i might fail and it might took time.
This WF has lazy version of your request - Last frame (The last node) . You can put it in Sourse image and continue from that. Sadly that quality slightly decreasing each itteration.
@GFrost Great to hear thanks! I read in the wf comments that you can send the last frame back to the wf which is great, but being able to use a first to last frame transition would me much better indeed.
The results are good, but it took 20 minutes to render a 7-second video (125 length) on 4080. Why use Fusion x Lora if workflows need more than 8 steps? Dont know any logic behind that just asking. Thnx for the workflow btw.
For anyone interested, i'm combining this wf which for me it's the best image quality in any wan wf, with this lora https://civitai.com/models/1713337/wan-self-forcing-rank-16-accelerator , i set both loras to strength to 1, sampler - euler, scheduler - beta, cfg 1, steps 4, i'm getting similar quality to the original wf but 5 sec vids take 1-2 min, give it a try.
Woah! i will give it it try. =)
Thnx!
Are you putting that accelerator Lora in the "Power Lora Loader" at the start, or in the "LoraModelLoaderOnly" in the Dual Samplers section, replacing the FusionX Loras?
Also, do you keep the "End at step" at 4 and are you setting the CFG and Steps the same in both KSamplers?
@Eshinio Lol you ever figure this out?
When i tryed i replaced fusionX with his lora and set same parameters in both. But in the end i returned to fusionx. It slower but results more satisfying for me.
what motion lora did you use?
Hi, FusionX.
Привет! При открытии часть недостающих узлов через ComfyUI Manager установились, но всё ещё не хватает этих
"When loading the graph, the following node types were not found
Text Find and Replace
Text Concatenate
String
FinalFrameSelector
UnetLoaderGGUFDisTorchMultiGPU
Switch any [Crystools]"
Может, есть идеи что я делаю не так?
Привет!
Странно, у меня все поставилось без проблемов
поискал в кастомных нодах
* Text Find and Replace
вот это WAS Node Suite (не Revised) В менеджере
* Text Concatenate
опять же в WAS Node Suite
* String
У меня сейчас установлена версия 1.2.9. -В менеджере - ComfyUI-Easy-Use
*FinalFrameSelector
В менеджере MediaMixer
*UnetLoaderGGUFDisTorchMultiGPU
в менеджере - ComfyUI-MultiGPU
Switch any [Crystools]"
В менеджере ComfyUI-Crystools
GFrost, к сожалению, получилось поставить всё кроме WAS Node Suite, в менеджере на нем висит "IMPORT FAILED" и такая ошибка
Error message occurred while importing the 'WAS Node Suite' module.
D:\ComfyUI_windows_portable\ComfyUI\custom_nodes\was-node-suite-comfyui\WAS_Node_Suite.py:7355: SyntaxWarning: invalid escape sequence '\o'
if output_path.endswith("ComfyUI/output") or output_path.endswith("ComfyUI\output"):
Traceback (most recent call last):
File "D:\ComfyUI_windows_portable\ComfyUI\nodes.py", line 2124, in load_custom_node
module_spec.loader.exec_module(module)
File "<frozen importlib._bootstrap_external>", line 999, in exec_module
File "<frozen importlib._bootstrap>", line 488, in callwith_frames_removed
File "D:\ComfyUI_windows_portable\ComfyUI\custom_nodes\was-node-suite-comfyui\__init__.py", line 1, in <module>
from .WAS_Node_Suite import NODE_CLASS_MAPPINGS
File "D:\ComfyUI_windows_portable\ComfyUI\custom_nodes\was-node-suite-comfyui\WAS_Node_Suite.py", line 14678, in <module>
build_info = ' '.join(cv2.getBuildInformation().split())
^^^^^^^^^^^^^^^^^^^^^^^
AttributeError: module 'cv2' has no attribute 'getBuildInformation'
UPD. Смог найти альтернативу узлу Text Concatenate, а вот подобных Text Find and Replace не нашлось. Пришлось просто удалить их и пустить в обход. Но тут наткнулся на проблему уже с FILM VFI, ошибка PytorchStreamReader failed reading zip archive: failed finding central directory.
Может быть сам ComfyUI как-то криво поставил.
В любом случае, хорошая работа, даже отключив часть результат мне нравится гораздо больше чем в других рабочих процессах что я пробовал, надеюсь у меня еще получится опробовать его в полной мере.
slowmind Я почитал оригинал WAS все, типа ушел. Я не пробовал но может надо WAS revised поставить и те две ноды на ихние заманить
GFrost да revised, тоже не ставится почему-то, пробовал
slowmind,
Чёрть, не пойму тогда в чем ошибка =(
Может надо обновить Комфи? Я вот использую портабл версию и периодически жмаю там update .
Версия которой я пользуюсь в описании, где Sage Attention
GFrost вновь попробовал поставить Revise и узлы заработали! Мне осталось лишь понять как починить Frame Interpolation. Огромное спасибо за помощь
UPD. Получилось, теперь всё работает идеально