In this repository, we present Wan2.1, a comprehensive and open suite of video foundation models that pushes the boundaries of video generation. Wan2.1 offers these key features: This repository hosts our T2V-1.3B model, a versatile solution for video generation that is compatible with nearly all consumer-grade GPUs. In this way, we hope that Wan2.1 can serve as an easy-to-use tool for more creative teams in video creation, providing a high-quality foundational model for academic teams with limited computing resources. This will facilitate both the rapid development of the video creation community and the swift advancement of video technology. Your browser does not support the video tag.…
Open weights
apache-2.0
1.4B parameters
diffusers
The recommended FastH3 Preview v1 checkpoint from FastVideo. It generates synchronized video and audio from text with four transformer forwards. This step-1300 model was trained with data-free DMD2 and VSA-H3 at 90% sparsity. Install uv, then use the CUDA 13 / Blackwell path below. It selects FastVideo's published CUDA kernel wheel instead of compiling the kernel locally. See the for other platforms. The tested defaults use four B200 GPUs and the trained four-forward schedule. On other multi-GPU CUDA systems, follow the installation guide and add --no-replicated-dit --vsa-kernel triton --no-fa4. The GPU count must divide H3's 56 attention heads. This preview supports text-to-audio-video…
Open weights
other
35B parameters
diffusers
We are excited to introduce Wan2.2, a major upgrade to our foundational video models. With Wan2.2, we have focused on incorporating the following innovations: This repository contains our TI2V-5B model, built with the advanced Wan2.2-VAE that achieves a compression ratio of 16×16×4. This model supports both text-to-video and image-to-video generation at 720P resolution with 24fps and can runs on single consumer-grade GPU such as the 4090. It is one of the fastest 720P@24fps models available, meeting the needs of both industrial applications and academic research. Your browser does not support the video tag. If your research or project builds upon Wan2.1 or Wan2.2, we welcome you to share it…
Open weights
apache-2.0
5B parameters
diffusers
We are excited to introduce Wan2.2, a major upgrade to our foundational video models. With Wan2.2, we have focused on incorporating the following innovations: This repository contains our T2V-A14B model, which supports generating 5s videos at both 480P and 720P resolutions. Built with a Mixture-of-Experts (MoE) architecture, it delivers outstanding video generation quality. On our new benchmark Wan-Bench 2.0, the model surpasses leading commercial models across most key evaluation dimensions. Your browser does not support the video tag. If your research or project builds upon Wan2.1 or Wan2.2, we welcome you to share it with us so we can highlight it for the broader community. - Wan2.2…
Open weights
apache-2.0
14.3B parameters
diffusers
LTX-2.5 is an open world model with open weights, built for local execution and fine-tuning. Its established use is generating synchronized, high-fidelity video and audio from text, image, and video inputs; applicability to emerging domains such as robotics and physical AI is developing. Full control and customization — self-host on your own infrastructure. No per-generation billing, no per-seat lock-in, no forced API dependency. Revenue is measured across the whole entity, including subsidiaries and affiliates under common control. The full, binding terms live in LICENSE. Encoding always uses vae/, and LTX2Pipeline decodes with vae/ too. The diffusion decoder is a diffusion model in its…
Access requested at publisher
other
19B parameters
diffusers
You can try our models here！ We're excited to introduce the FastWan2.2 series—a new line of models finetuned with our novel Sparse-distill strategy. This approach jointly integrates DMD and VSA in a single training process, combining the benefits of both distillation to shorten diffusion steps and sparse attention to reduce attention computations, enabling even faster video generation. FastWan2.2-TI2V-5B-Full-Diffusers is built upon Wan-AI/Wan2.2-TI2V-5B-Diffusers. It supports efficient 3-step inference and produces high-quality videos at 121×704×1280 resolution. For training, we used simulated forward for the generator model, making the process data-free. The current…
Open weights
apache-2.0
5B parameters
diffusers
AnimateLCM: Computation-Efficient Personalized Style Video Generation without Personalized Video Data by Fu-Yun Wang et al. For more details, please refer to our [paper] | [code] | [proj-page] | [civitai].
Open weights
454M parameters
diffusers
This GGUF file is a direct conversion of Wan-AI/Wan2.2-T2V-A14B Since this is a quantized model, all original licensing terms and usage restrictions remain in effect. Usage The model can be used with the ComfyUI custom node ComfyUI-GGUF by city96 Place model files in ComfyUI/models/unet see the GitHub readme for further installation instructions.
Open weights
apache-2.0
gguf
A LoRA for MiniMax-H3 that renders joint video + synchronized stereo audio in as few as 4 sampling steps instead of the usual ~20 — a ~5× sampling speedup — and keeps getting better as you add steps. For most work, use minimaxh3turbov4step600ema.safetensors. It's the markedly better micro-detail (faces, fingers, fine texture), and the over-sharpening / plastic look of the earlier v1 (~850) line is fully resolved. v4 introduced a static-frame enhancement — a big win for static and small-motion content. The one trade-off shows up only at 4 steps with large, fast motion, where v4 can produce motion-smear / trailing ghosting (we're actively fixing this). Two things address it: - Use 6–8 steps.…
Open weights
apache-2.0
minimax-h3
This repository contains MiniMax-H3 Turbo LoRAs converted and optimized for ComfyUI: These LoRAs accelerate MiniMax-H3 video and synchronized-audio generation by reducing the required number of sampling steps. Newly added LoRA, located in the experimental/ folder: Manual recommended sigmas: 3-step 1.0, 0.961165, 0.853333, 0.0 4-step 1.0, 0.970874, 0.907249, 0.640000, 0.0 Three LoRAs extracted from VDN-H3 8 step: The main 8-step LoRA works on both FL2VA and Ref2VA. If you are running a pruned base, choose the pruned version that corresponds to your base — the pruned versions need their own matching pruned base. Three dynamically resized BF16 LoRAs are now included. Their source weights were…
Open weights
apache-2.0
minimax-h3
Sulphur 2 An uncensored video generation model based on LTX 2.3 supporting both t2v and i2v natively, as well as all of the other ltx 2.3 formats. Follow us on X Join our Discord Support the next version of the project, even just a few dollars would go a long way: Kofi To get started with the model, I recommend downloading either of the dev versions, (fp8mixed or bf16) and downloading the distill lora provided. By the way, I'm aware the workflows contain sulphurfinal right now, just use the lora or use the full models, don't use both at the same time. This model contains a prompt enhancer. The easiest way to get started with the prompt enhancer is by using it on lmstudio. The way to…
Open weights
diffusers
Model · Text to video
Sam
Wan2.1 is an open-source suite of video foundation models, compatible with consumer-grade GPUs, that excels in various video generation tasks like text-to-video, image-to-video, and video editing, even supporting visual text generation. Download models using huggingface-cli: You can also download directly from this page. This model is a derivative work of the original model licensed under the Apache 2.0 License, and is therefore distributed under the terms of the same license. Thanks to Patrick Gillespie for creating the ASCII text art tool used in this project https://patorjk.com/software/taag/ Wan-AI for the Wan model https://huggingface.co/Wan-AI/Wan2.1-VACE-1.3B…
Open weights
apache-2.0
diffusers
Model · Text to video
Sam
Wan2.1 is an open-source suite of video foundation models, compatible with consumer-grade GPUs, that excels in various video generation tasks like text-to-video, image-to-video, and video editing, even supporting visual text generation. Download models using huggingface-cli: You can also download directly from this page. This model is a derivative work of the original model licensed under the Apache 2.0 License, and is therefore distributed under the terms of the same license. Thanks to Patrick Gillespie for creating the ASCII text art tool used in this project https://patorjk.com/software/taag/ Wan-AI for the Wan model https://huggingface.co/Wan-AI/Wan2.1-T2V-1.3B…
Open weights
apache-2.0
diffusers
Model · Text to video
Jay
This repository contains GGUF format model files for SulphurAI's Sulphur-2-base. The following quantization tiers are provided to accommodate different hardware capabilities and VRAM constraints.
Open weights
gguf
This GGUF file is a direct conversion of Wan-AI/Wan2.2-TI2V-5B Since this is a quantized model, all original licensing terms and usage restrictions remain in effect. Usage The model can be used with the ComfyUI custom node ComfyUI-GGUF by city96 Place model files in ComfyUI/models/unet see the GitHub readme for further installation instructions.
Open weights
apache-2.0
gguf
In this repository, we present Wan2.1, a comprehensive and open suite of video foundation models that pushes the boundaries of video generation. Wan2.1 offers these key features: This repository features our T2V-14B model, which establishes a new SOTA performance benchmark among both open-source and closed-source models. It demonstrates exceptional capabilities in generating high-quality visuals with significant motion dynamics. It is also the only video model capable of producing both Chinese and English text and supports video generation at both 480P and 720P resolutions. Your browser does not support the video tag. - Wan2.1 Text-to-Video - [x] Multi-GPU Inference code of the 14B and 1.3B…
Open weights
apache-2.0
14.3B parameters
diffusers
We apply Parallel Decoding Distillation (PDD) 1 to MiniMax-H3, enabling efficient video generation in only a few inference steps. For more details, please refer to our GitHub repo. Set modelpath and pddlorapath to the MiniMax-H3 model and the matching acceleration LoRA checkpoint in predictt2v.py for FL2VA or predictref2v.py for Ref2VA, then run the corresponding script. Each example uses applypddlora to load the checkpoint and derive the required number of inference steps from its configuration.
Open weights
other
videox_fun
Model · Text to video
Jay
This repository provides quantized GGUF formats of the distilled transformer from Lightricks/LTX-2.5. These weights are highly optimized for local execution, allowing you to run high-fidelity video and audio generation workflows on hardware with memory constraints while retaining the core visual fidelity of the original base model. LTX-2.5 operates on a split-component architecture. To run these GGUF diffusion models in environments like ComfyUI or local Python pipelines, you must also fetch the official Text Encoders and VAEs directly from the upstream Lightricks/LTX-2.5 repository. Download these from the textencoders directory: gemma4-12b-with-proj-ltx-2.5-bf16.safetensors (26.3 GB)…
Open weights
other
Every GGUF quantisation of Wan2.2-TI2V-5B that QuantStack/Wan2.2-TI2V-5B-GGUF publishes, plus the companion VAE, mirrored here. Unsloth Studio offers this repo as the curated one-click GGUF pick for Wan2.2 TI2V 5B, so its availability is Studio's problem rather than the repacker's: a rename or a takedown turns the pick into a 404 no client can work around. All 13 quants are mirrored, not a chosen few, because the picker lets you choose the precision. The weights are unmodified: byte for byte the files of the same name in the source repo. TI2V-5B is a 720P-only checkpoint: the supported sizes are 1280x704 and 704x1280, and its VAE has temporal compression 4, so valid frame counts are 4k+1.…
Open weights
apache-2.0
gguf
UPDATED 8/21/2026 - The latest LTX Video-2.3 Uncensored Turbo v1.4 DiT with Distilled LoRA baked in. Modes: img2video, txt2video, FL2VA / T2VA / I2VA / REF2VA/ AUDIO-TO-VIDEO. A pre-merged, GGUF and FP8 build of LTX Video-2.3 with three fine-tunes baked into the weights: 1. Eros10 NSFW LoRA - Eros10 is known for high quality, coherence, and NSFW (1.0 strength) 2. DMD Distilled LoRA - DMD distilled LoRA promises faster generations, better facial preservation (I2V), and MUCH better instruction following than v1 or stock LTXV23. (1.0 strength) 3. LTX Video ICLoRA Detailer - Official LTXV In-Context LoRA for better reference image adherence. (0.6 strength) The model can produce video in as…
Open weights
unknown
gguf
convert TurboWan2.1-T2V-1.3B-480P(https://modelscope.cn/models/TurboDiffusion/TurboWan2.1-T2V-1.3B-480P/summary) to TurboWan2.1-T2V-1.3B-Diffusers convert script https://github.com/IPostYellow/TurboWantoDiffusers/blob/main/convertturbowantodiffusers.py To use in sglang
Open weights
apache-2.0
1.4B parameters
diffusers
In this repository, we present Wan2.1, a comprehensive and open suite of video foundation models that pushes the boundaries of video generation. Wan2.1 offers these key features: This repository features our T2V-14B model, which establishes a new SOTA performance benchmark among both open-source and closed-source models. It demonstrates exceptional capabilities in generating high-quality visuals with significant motion dynamics. It is also the only video model capable of producing both Chinese and English text and supports video generation at both 480P and 720P resolutions. Your browser does not support the video tag. - Wan2.1 Text-to-Video - [x] Multi-GPU Inference code of the 14B and 1.3B…
Open weights
apache-2.0
14.3B parameters
diffusers
ComfyUI-key repackaging of the official 8-step PDD acceleration LoRAs for MiniMax-H3 — full audio+video generation in 8 (or 4) sampler steps, CFG-free. These are not plain LoRAs. Each file carries a rank-64 trunk LoRA plus a Parallel Decoding Distillation head bank (32 per-interval final-layer projections per modality, PDD — arXiv:2607.26004). Loading them requires the (also loads the original alibaba-pai files directly — this repo just saves you the in-memory conversion and gives you inspectable standard LoRA keys). Put the LoRA files in ComfyUI/models/pddacc/. Pair FL2VA with an fl2va UNET, Ref2VA with ref2va (bf16 or int8-convrot builds both work). The baked checkpoint goes in…
Open weights
apache-2.0
minimax-h3
Free ComfyUI workflows, Runpod templates, and guides: https://discord.gg/ZVWVhT43GW https://get.runpod.io/minimax-template A mirror of the MiniMax-H3 LoRAs published on CivitAI. CivitAI-matched files have identical SHA-256 checksums (listed below); the HMMisDogV2 exception is noted in the recent uploads table. CivitAI carries the sample videos, the version history and the comment threads; this repository exists so the weights can be pulled with a plain resolve URL, without an account. One anatomy adapter teaches H3 what a body part looks like. One action adapter teaches it what a body does. They are single-concept and they stack, so put them under whatever character or scene LoRA you are…
Open weights
other
minimax-h3
We are excited to introduce Wan2.2, a major upgrade to our foundational video models. With Wan2.2, we have focused on incorporating the following innovations: This repository contains our T2V-A14B model, which supports generating 5s videos at both 480P and 720P resolutions. Built with a Mixture-of-Experts (MoE) architecture, it delivers outstanding video generation quality. On our new benchmark Wan-Bench 2.0, the model surpasses leading commercial models across most key evaluation dimensions. Your browser does not support the video tag. If your research or project builds upon Wan2.1 or Wan2.2, we welcome you to share it with us so we can highlight it for the broader community. - Wan2.2…
Open weights
apache-2.0
14.3B parameters
diffusers
Model · Text to video
Joey
The comfy-native cuts of the MiniMax-H3 × Z-Image graft: Z-Image's spatial-attention profile on H3's engine — richer sets and textures, same identity, no per-shot sharpening creep. Full story, demos and verification on the GGUF page. Load with the plain Load Diffusion Model node, ComfyUI 0.32+. Files are the pruned H3 builds with the graft baked in (zs05 = late-block gains, dose 0.5): - bf16 — the master (ref2va) - comfy-fp8 / fp8e5m2 — fp8 scaled - comfy-int8 / int8convrot — the fast pick on RTX 50 - comfy-w4a8 / w4a4 / nvfp4 — 4-bit family for 16 GB cards (w4a8 is the quality pick; nvfp4 is Blackwell-native, emulated elsewhere) - comfy-mxfp8 — 8-bit microscaling, Blackwell-specialized…
Open weights
other
minimax-h3
Model · Text to video
City
This is a direct GGUF conversion of Wan-AI/Wan2.1-T2V-14B All quants are created from the FP32 base file, though I only uploaded FP16 due to it exceeding the 50GB max file limit and gguf-split loading not currently being supported in ComfyUI-GGUF. The model files can be used with the ComfyUI-GGUF custom node. Place model files in ComfyUI/models/unet - see the GitHub readme for further install instructions. The VAE can be downloaded from this repository by Kijai Please refer to this chart for a basic overview of quantization types.
Open weights
apache-2.0
gguf
In this repository, we present Wan2.1, a comprehensive and open suite of video foundation models that pushes the boundaries of video generation. Wan2.1 offers these key features: This repository hosts our T2V-1.3B model, a versatile solution for video generation that is compatible with nearly all consumer-grade GPUs. In this way, we hope that Wan2.1 can serve as an easy-to-use tool for more creative teams in video creation, providing a high-quality foundational model for academic teams with limited computing resources. This will facilitate both the rapid development of the video creation community and the swift advancement of video technology. Your browser does not support the video tag.…
Open weights
apache-2.0
1.4B parameters
diffusers
Example workflow - based on the Comfyui example workflow This is a direct GGUF conversion of Wan-AI/Wan2.1-VACE-14B All quants are created from the FP32 base file, though I only uploaded the Q80 and less, if you want the F16 or BF16 one I would upload it per request. The model files can be used with the ComfyUI-GGUF custom node. Place model files in ComfyUI/models/unet - see the GitHub readme for further install instructions. The VAE can be downloaded from here Please refer to this chart for a basic overview of quantization types. For conversion I used the conversion scripts from city96
Open weights
apache-2.0
gguf
This is a video detailer model on top of LTXV13B098DEV trained on custom data. IC LoRA is a method that enables adding video context into the video generation process. This approach allows for video-to-video control on top of the text-to-video model, providing more precise control over the generated content by conditioning the model on reference video frames during inference. For licensing information, please refer to the LTXV Open Weights License. This model is designed to be used with the LTXV (Lightricks Text-to-Video) pipeline. In order to use the trained lora in comfy: 1. Copy the comfyui trained LoRA weights to the models/loras folder in your ComfyUI installation. 2. Use…
Open weights
other
diffusers
Model · Text to video
Cαlcμ
drag gguf to >./ComfyUI/models/diffusionmodels - drag t5xxl-um to >./ComfyUI/models/textencoders - drag vae to >./ComfyUI/models/vae - for i2v model, drag clip-vision-h to >./ComfyUI/models/clipvision - run the.bat file in the main directory (assume you are using gguf pack below) - if you opt to use fp8 scaled umt5xxl encoder (if applies to any fp8 scale t5 actually), please use cpu offload (switch from default to cpu under device in gguf clip loader; won't affect speed); btw, it works fine for both gguf umt5xxl and gguf vae - drag any demo video (below) to > your browser for workflow - pig is a lazy architecture for gguf node; it applies to all model, encoder and vae gguf file(s); if you…
Open weights
apache-2.0
GGUF quantizations of Lightricks' LTX-2.5, converted for ComfyUI with ComfyUI-GGUF. LTX-2.5 generates video and synchronized audio in a single pass — a dual-stream DiT with a 4096-wide video path, a 2048-wide audio path, and cross-modal attention joining them. The bf16 transformer is 39 GB. These quants bring it to 8-22 GB. All original licensing terms and usage restrictions carry over from the base model. If you convert LTX-2.5 to GGUF yourself, it will not load. These files have the fix baked in; this section explains what it is, because it isn't obvious and it cost a night to find. ComfyUI derives most model dimensions from tensor shapes. For LTX-2.5 it can't: the connector widths, the…
Open weights
other
gguf
Model · Text to video
Hpmg
空间思维与物理逻辑 LoRA，基于 MiniMax-H3（Comfy-Org/MiniMax-H3）训练，让模型学会纯物体的空间关系与物理运动（碰撞、堆叠、掉落、遮挡等）。 目前还是训练和测试阶段，一些素材片段以及打标问题导致LORA还不是特别稳定。下一阶段准备修复后重新训练。目前LORA也是可以使用，强度建议0.3 ~ 0.5。纯属是在原模型基础上稍微增强一点物理反馈。 最新是重新训练到了wushuspatialphysicsclean3000pruned.safetensors 版本。 实测用了这个LORA，视频整体提升真实感物理的逻辑，比如物体碰撞的真实反馈。也可以用于一些打斗场景，人物真实碰撞的效果。 用了空间物理LORA的武打片段（强度 0.3） 没有用空间物理LORA的武打片段（同样提示词） 1. 下载.safetensors，放入 ComfyUI models/loras/ 2. LoraLoader 加载，strength 建议 0.8~1.0 3. 用空间/物理语言 prompt 描述物体运动 - several colored objects 多个彩色物体（CLEVRER 风格） - rigid objects 刚体 / elastic objects 弹性物体 - metal objects 金属物体 - a ball / balls 球 - billiard balls 台球 - objects 通用物体 - on a table 桌面上（PhyCo 台球场景） - in a synthetic scene 合成场景（CLEVRER 风格）…
Open weights
apache-2.0
minimax-h3
We explore the Reward Backpropagation technique 1 2 to optimized the generated videos by Wan2.2-Fun for better alignment with human preferences. We provide the following pre-trained models (i.e. LoRAs) along with the training script. You can use these LoRAs to enhance the corresponding base model as a plug-in or train your own reward LoRA. For more details, please refer to our GitHub repo. A panda eats bamboo while a monkey swings from branch to branch A dog runs through a field while a cat climbs a tree A penguin waddles on the ice, a camel treks by Pig with wings flying above a diamond mountain Set lorapath along with loraweight for the low noise reward LoRA, while specifying lorahighpath…
Open weights
apache-2.0
videox_fun
We are excited to introduce Wan2.2, a major upgrade to our foundational video models. With Wan2.2, we have focused on incorporating the following innovations: This repository contains our TI2V-5B model, built with the advanced Wan2.2-VAE that achieves a compression ratio of 16×16×4. This model supports both text-to-video and image-to-video generation at 720P resolution with 24fps and can runs on single consumer-grade GPU such as the 4090. It is one of the fastest 720P@24fps models available, meeting the needs of both industrial applications and academic research. Your browser does not support the video tag. If your research or project builds upon Wan2.1 or Wan2.2, we welcome you to share it…
Open weights
apache-2.0
wan2.2
This repository is a ready-to-place model bundle for the OpenVDN workflows in It contains the exact local model set used for the project's corrected DMD8 validation. The Seedance and RunningHub URLs above contain referral or invite codes supplied by T8star. 1. Install or update the custom node: 2. Log in to Hugging Face after your access request is approved, then download this repository directly into ComfyUI/models: 3. Restart ComfyUI and load one of the OpenVDN workflows from examples/workflows/10-speed in the custom-node repository. The repository already uses ComfyUI's folder names, so no file rearrangement is needed. Exact byte sizes and SHA-256 hashes are listed in MODELMANIFEST.json.…
Open weights
other
minimax-h3
Model · Text to video
Z.ai
Visit QingYing and API Platform to experience commercial video generation models. CogVideoX is an open-source version of the video generation model originating from QingYing. The table below displays the list of video generation models we currently offer, along with their foundational information. Data Explanation + When testing using the diffusers library, all optimizations provided by the diffusers library were enabled. This solution has not been tested for actual VRAM/memory usage on devices other than NVIDIA A100 / H100. Generally, this solution can be adapted to all devices with NVIDIA Ampere architecture and above. If the optimizations are disabled, VRAM usage will increase…
Open weights
apache-2.0
1.7B parameters
diffusers
A diffusers-directory-layout repackaging of Efficient-Large-Model/LongLive-2.0-5B so it loads directly in SGLang Diffusion (sglang.multimodalgen) without any runtime overlay/materialization. - transformer/ — the generator weights extracted from the original modelbf16.pt, kept in their original (model.) naming; SGLang's LongLive2Transformer3DModel.paramnamesmapping maps them to the diffusers module names at load (same convention as LingBot-World). - scheduler / textencoder / tokenizer / vae — taken from Wan-AI/Wan2.2-TI2V-5B-Diffusers. - modelindex.json classname = LongLive2Pipeline.
Open weights
5B parameters
diffusers
Quantized diffusion transformers for MiniMax H3, a 33B omni-modal video+audio generator, built from the ComfyUI repack at Comfy-Org/MiniMax-H3. Output is 768p / 24 fps / 4–15 s with synchronized 32 kHz stereo audio. (2K output requires the separate H3-Regenerate-2K module, which is not part of this or Comfy-Org's release.) These are ComfyUI single-file checkpoints, not diffusers models. Filenames follow minimaxh3.safetensors. - fl2va — first/last-frame mode. Zero images = text-to-video, one or two = frame-conditioned. - ref2va — omni-reference mode (up to 9 images / 3 video clips / 3 audio clips). Both get identical treatment; pick the one matching your workflow. The three INT4 variants…
Open weights
other
minimax-h3
Cinematic behind-the-scenes movie sets for LTX-2.5. A LoRA by SOLRICKS for the atmosphere of high-budget film production: professional camera rigs, cranes, dolly tracks, studio lighting, green/blue screens, practical sets and working film crews. Supports both T2V and I2V generation with LTX-2.5. The released LoRA weights are available directly in this repository: Download BTSMovieSetLTX25v1.safetensors. A copy is also available on Civitai. 1. Download BTSMovieSetLTX25v1.safetensors from this model page. 2. Place the file in ComfyUI/models/loras/ and load it in your LTX-2.5 workflow. 3. Start with a LoRA weight of 0.8 and include btssetstyle in the positive prompt. 4. For T2V, describe the…
Open weights
other
