Instructions to use SyFeee/Bernini-LTX-Research-Checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Inference
- Notebooks
- Google Colab
- Kaggle
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license: other
license_name: ltx-2-community-license
license_link: https://huggingface.co/Lightricks/LTX-2.3/blob/main/LICENSE
base_model: Lightricks/LTX-2.3
pipeline_tag: text-to-video
tags:
- ltx-video
- ltx-2.3
- lora
- video-generation
- research
---
# Bernini LTX Research Checkpoints
This repository contains 12 experimental Bernini adaptation runs trained against the LTX-2.3 22B development checkpoint. These are early research artifacts, not production-validated releases.
## Important Loading Requirement
Each run contains two files that must be loaded together:
- `lora_weights_step_*.safetensors`: the rank-64 LoRA adapter.
- `bernini_P_step_*.safetensors`: the matching Bernini projection weights.
The LoRA alone is incomplete. Keep both files from the same run and step; projection weights are not interchangeable across runs.
## Included Runs
| Run | Step | Research focus |
| --- | ---: | --- |
| `bernini_av_phaseA` | 1000 | Reference-to-video plus joint audio |
| `bernini_av_phaseA_704` | 1000 | Phase A at the 704 training setup |
| `bernini_av_phaseB_704` | 1000 | Reference-voice conditioning at 704 |
| `bernini_combined_pilot` | 1800 | Combined conditioning pilot |
| `bernini_duo_pilot_inline` | 1000 | Inline two-subject conditioning |
| `bernini_fight_motion_pilot` | 1500 | High-motion pose-control pilot |
| `bernini_multishot_704` | 1000 | Multi-shot continuity at 704 |
| `bernini_p2_baseline` | 1500 | P2 baseline |
| `bernini_p2_plan` | 1500 | P2 planning-conditioned run |
| `bernini_r2v_msr_baseline` | 1500 | R2V MSR baseline |
| `bernini_r2v_plan_pure` | 1500 | R2V plan-only variant |
| `bernini_r2v_plan_ref` | 1500 | R2V planning with references |
Each `runs/<run>/training_config.yaml` records the corresponding experiment configuration. Paths in these archival configs reflect the original training machine and must be adapted locally.
## Scope and Use
The checkpoints explore identity/reference conditioning, planning, multi-subject control, motion control, multi-shot behavior, and audio generation. Quality varies by run. Validate identity, motion, audio, and temporal consistency on representative prompts before deployment.
Use of these derivatives remains subject to the LTX-2 Community License and the terms of the base model.
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