--- license: apache-2.0 language: - en base_model: - genmo/mochi-1-preview pipeline_tag: text-to-video tags: - jinx - arcane - mochi - diffusion --- # Fine-Tuning Mochi-Sota Text-to-Video: Jinx Lora Test This project demonstrates the fine-tuning of the **Mochi-Sota Text-to-Video** model using a LoRA (Low-Rank Adaptation) approach, focusing on the character **Jinx** from the *League of Legends* universe. The goal was to adapt the model to generate dynamic, character-specific video sequences with consistent visual and motion styles. ## Training Details - **Model Base**: Mochi-Sota Text-to-Video - **Fine-Tuning Dataset**: 14 short video clips of Jinx - **Frame Selection**: 61 frames extracted from the videos - **Training Hardware**: H100 GPU - **Training Duration**: 5 hours This fine-tuning process leverages LoRA to efficiently adapt the model while preserving the core capabilities of the base model. --- ## Results Below is an example of the generated video output: ### **Sample Description** *Jinx sprints through a dimly lit alley, her vibrant blue hair trailing behind her. She clutches a small, bulging sack tightly against her chest. Dressed in a dark crop top and boots, she moves with chaotic energy, her boots thudding loudly on the pavement. Her mischievous grin flashes briefly as she glances back, her pace never faltering.* ### **Generated Sample** ---