LTX2.3 10Eros 1.2 GGUF

--- base_model: - TenStrip/LTX2.3-10Eros library_name: diffusers pipeline_tag: image-to-video tags: - image-to-video - ltx-2-3 - ltx-video - sulphur-2 - 10Eros --- **GGUF Version of LTX2.3-10Eros-1.2 for ComfyUI** **Original model Link:** [https://huggingface.co/TenStrip/LTX2.3-10Eros](https://huggingface.co/TenStrip/LTX2.3-10Eros) **Watch us on Youtube:** [@VantageWithAI](https://www.youtube.com/@vantagewithai) - *For v1 follow this link* [https://huggingface.co/vantagewithai/LTX2.3-10Eros-GGUF](https://huggingface.co/vantagewithai/LTX2.3-10Eros-GGUF) - *For v1.3 follow this link* [https://huggingface.co/vantagewithai/LTX2.3-10Eros-1.3-GGUF](https://huggingface.co/vantagewithai/LTX2.3-10Eros-1.3-GGUF) - *For v1.4 follow this link* [https://huggingface.co/vantagewithai/LTX2.3-10Eros-1.4-GGUF](https://huggingface.co/vantagewithai/LTX2.3-10Eros-1.4-GGUF) **10 Eros** v1.2 Changelog: Leveraged tuned connector data to reduce face drift and aid long prompts/director. Also using sulphur EXP weights on top of v1 to hone the most explicit motions. All common issues like mistaken extra anatomy, subtitles, unexpected transitions, etc all still present from v1. Nodes: https://github.com/TenStrip/10S-Comfy-nodes Reliant on https://huggingface.co/SulphurAI/Sulphur-2-base This is a different merge attempt for ideal I2V use. It uses layer scaled merges of different steps, it's not a straight weight merge. It behaves much nicer than lora load and respects prompt. Prompt should be enhanced, LTX has very little self reasoning and input when it is conditioned, first frame and all following motions, evolutions, and audio must be commanded-you will get nothing if you don't ask it. !!! Larger distilled Loras will harm the model's fine tune, try the cond_safe ones: https://huggingface.co/TenStrip/LTX2.3_Distilled_Lora_1.1_Experiments/tree/main For prompt enhancement, try this foreword in Grok or Uncensored LLM: Generate a video scene script with a description based on the attached image for an LLM that has a tokenizer that uses interleaved attention to support long-context understanding that is fed into a multimodal video model. Strict specification, follow up to the word: No timestamps. No unnecessary embellishment. Output only plain English text and make it a copy box. First, describe the image initial scene in concise natural language; subject(s), subject(s) appe...

--- base_model: - TenStrip/LTX2.3-10Eros library_name: diffusers pipeline_tag: image-to-video tags: - image-to-video - ltx-2-3 - ltx-video - sulphur-2 - 10Eros --- **GGUF Version of LTX2.3-10Eros-1.2 for ComfyUI** **Original model Link:** [https://huggingface.co/TenStrip/LTX2.3-10Eros](https://huggingface.co/TenStrip/LTX2.3-10Eros) **Watch us on Youtube:** [@VantageWithAI](https://www.youtube.com/@vantagewithai) - *For v1 follow this link* [https://huggingface.co/vantagewithai/LTX2.3-10Eros-GGUF](https://huggingface.co/vantagewithai/LTX2.3-10Eros-GGUF) - *For v1.3 follow this link* [https://huggingface.co/vantagewithai/LTX2.3-10Eros-1.3-GGUF](https://huggingface.co/vantagewithai/LTX2.3-10Eros-1.3-GGUF) **10 Eros** v1.2 Changelog: Leveraged tuned connector data to reduce face drift and aid long prompts/director. Also using sulphur EXP weights on top of v1 to hone the most explicit motions. All common issues like mistaken extra anatomy, subtitles, unexpected transitions, etc all still present from v1. Nodes: https://github.com/TenStrip/10S-Comfy-nodes Reliant on https://huggingface.co/SulphurAI/Sulphur-2-base This is a different merge attempt for ideal I2V use. It uses layer scaled merges of different steps, it's not a straight weight merge. It behaves much nicer than lora load and respects prompt. Prompt should be enhanced, LTX has very little self reasoning and input when it is conditioned, first frame and all following motions, evolutions, and audio must be commanded-you will get nothing if you don't ask it. !!! Larger distilled Loras will harm the model's fine tune, try the cond_safe ones: https://huggingface.co/TenStrip/LTX2.3_Distilled_Lora_1.1_Experiments/tree/main For prompt enhancement, try this foreword in Grok or Uncensored LLM: Generate a video scene script with a description based on the attached image for an LLM that has a tokenizer that uses interleaved attention to support long-context understanding that is fed into a multimodal video model. Strict specification, follow up to the word: No timestamps. No unnecessary embellishment. Output only plain English text and make it a copy box. First, describe the image initial scene in concise natural language; subject(s), subject(s) appearance, subject(s) composition and pose, background, and context. Next, formulate a naturally evolving scenario that would take place describing every m...

Source context: 2781 downloads · 13 likes · Pipeline image-to-video · Library diffusers · Repo vantagewithai/LTX2.3-10Eros-1.2-GGUF