* Add Kandinsky5 model support
lite and pro T2V tested to work
* Update kandinsky5.py
* Fix fp8
* Fix fp8_scaled text encoder
* Add transformer_options for attention
* Code cleanup, optimizations, use fp32 for all layers originally at fp32
* ImageToVideo -node
* Fix I2V, add necessary latent post process nodes
* Support text to image model
* Support block replace patches (SLG mostly)
* Support official LoRAs
* Don't scale RoPE for lite model as that just doesn't work...
* Update supported_models.py
* Rever RoPE scaling to simpler one
* Fix typo
* Handle latent dim difference for image model in the VAE instead
* Add node to use different prompts for clip_l and qwen25_7b
* Reduce peak VRAM usage a bit
* Further reduce peak VRAM consumption by chunking ffn
* Update chunking
* Update memory_usage_factor
* Code cleanup, don't force the fp32 layers as it has minimal effect
* Allow for stronger changes with first frames normalization
Default values are too weak for any meaningful changes, these should probably be exposed as advanced node options when that's available.
* Add image model's own chat template, remove unused image2video template
* Remove hard error in ReplaceVideoLatentFrames -node
* Update kandinsky5.py
* Update supported_models.py
* Fix typos in prompt template
They were now fixed in the original repository as well
* Update ReplaceVideoLatentFrames
Add tooltips
Make source optional
Better handle negative index
* Rename NormalizeVideoLatentFrames -node
For bit better clarity what it does
* Fix NormalizeVideoLatentStart node out on non-op
* init
* update
* Update model.py
* Update model.py
* remove print
* Fix text encoding
* Prevent empty negative prompt
Really doesn't work otherwise
* fp16 works
* I2V
* Update model_base.py
* Update nodes_hunyuan.py
* Better latent rgb factors
* Use the correct sigclip output...
* Support HunyuanVideo1.5 SR model
* whitespaces...
* Proper latent channel count
* SR model fixes
This also still needs timesteps scheduling based on the noise scale, can be used with two samplers too already
* vae_refiner: roll the convolution through temporal
Work in progress.
Roll the convolution through time using 2-latent-frame chunks and a
FIFO queue for the convolution seams.
* Support HunyuanVideo15 latent resampler
* fix
* Some cleanup
Co-Authored-By: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>
* Proper hyvid15 I2V channels
Co-Authored-By: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>
* Fix TokenRefiner for fp16
Otherwise x.sum has infs, just in case only casting if input is fp16, I don't know if necessary.
* Bugfix for the HunyuanVideo15 SR model
* vae_refiner: roll the convolution through temporal II
Roll the convolution through time using 2-latent-frame chunks and a
FIFO queue for the convolution seams.
Added support for encoder, lowered to 1 latent frame to save more
VRAM, made work for Hunyuan Image 3.0 (as code shared).
Fixed names, cleaned up code.
* Allow any number of input frames in VAE.
* Better VAE encode mem estimation.
* Lowvram fix.
* Fix hunyuan image 2.1 refiner.
* Fix mistake.
* Name changes.
* Rename.
* Whitespace.
* Fix.
* Fix.
---------
Co-authored-by: kijai <40791699+kijai@users.noreply.github.com>
Co-authored-by: Rattus <rattus128@gmail.com>
* Initial Chroma Radiance support
* Minor Chroma Radiance cleanups
* Update Radiance nodes to ensure latents/images are on the intermediate device
* Fix Chroma Radiance memory estimation.
* Increase Chroma Radiance memory usage factor
* Increase Chroma Radiance memory usage factor once again
* Ensure images are multiples of 16 for Chroma Radiance
Add batch dimension and fix channels when necessary in ChromaRadianceImageToLatent node
* Tile Chroma Radiance NeRF to reduce memory consumption, update memory usage factor
* Update Radiance to support conv nerf final head type.
* Allow setting NeRF embedder dtype for Radiance
Bump Radiance nerf tile size to 32
Support EasyCache/LazyCache on Radiance (maybe)
* Add ChromaRadianceStubVAE node
* Crop Radiance image inputs to multiples of 16 instead of erroring to be in line with existing VAE behavior
* Convert Chroma Radiance nodes to V3 schema.
* Add ChromaRadianceOptions node and backend support.
Cleanups/refactoring to reduce code duplication with Chroma.
* Fix overriding the NeRF embedder dtype for Chroma Radiance
* Minor Chroma Radiance cleanups
* Move Chroma Radiance to its own directory in ldm
Minor code cleanups and tooltip improvements
* Fix Chroma Radiance embedder dtype overriding
* Remove Radiance dynamic nerf_embedder dtype override feature
* Unbork Radiance NeRF embedder init
* Remove Chroma Radiance image conversion and stub VAE nodes
Add a chroma_radiance option to the VAELoader builtin node which uses comfy.sd.PixelspaceConversionVAE
Add a PixelspaceConversionVAE to comfy.sd for converting BHWC 0..1 <-> BCHW -1..1
* support wan camera models
* fix by ruff check
* change camera_condition type; make camera_condition optional
* support camera trajectory nodes
* fix camera direction
---------
Co-authored-by: Qirui Sun <sunqr0667@126.com>
* Upload files for Chroma Implementation
* Remove trailing whitespace
* trim more trailing whitespace..oops
* remove unused imports
* Add supported_inference_dtypes
* Set min_length to 0 and remove attention_mask=True
* Set min_length to 1
* get_mdulations added from blepping and minor changes
* Add lora conversion if statement in lora.py
* Update supported_models.py
* update model_base.py
* add uptream commits
* set modelType.FLOW, will cause beta scheduler to work properly
* Adjust memory usage factor and remove unnecessary code
* fix mistake
* reduce code duplication
* remove unused imports
* refactor for upstream sync
* sync chroma-support with upstream via syncbranch patch
* Update sd.py
* Add Chroma as option for the OptimalStepsScheduler node
* draft pass at a native comfy implementation of Lotus-D depth and normal est
* fix model_sampling kludges
* fix ruff
---------
Co-authored-by: comfyanonymous <121283862+comfyanonymous@users.noreply.github.com>
To use:
"Load CLIP" node with t5xxl + type mochi
"Load Diffusion Model" node with the mochi dit file.
"Load VAE" with the mochi vae file.
EmptyMochiLatentVideo node for the latent.
euler + linear_quadratic in the KSampler node.
* Let tokenizers return weights to be stored in the saved checkpoint.
* Basic hunyuan dit implementation.
* Fix some resolutions not working.
* Support hydit checkpoint save.
* Init with right dtype.
* Switch to optimized attention in pooler.
* Fix black images on hunyuan dit.
This is the code to load the model and inference it with only a text
prompt. This commit does not contain the nodes to properly use it with an
image input.
This supports both the original SD1 instructpix2pix model and the
diffusers SDXL one.
comfyanonymous
Jukka Seppänen
blepping
Yousef R. Gamaleldin
Yoland Yan
George0726
comfyanonymous
Silver
thot experiment
City
Chenlei Hu