Text-to-Audio
LTX.io
English
ltx-audio
audio
audio-generation
speech
reference-conditioning
multi-speaker
flow-matching
diffusion
Instructions to use suryatmodulus/scena with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LTX.io
How to use suryatmodulus/scena with LTX.io:
# Install the LTX-2 pipelines git clone https://github.com/Lightricks/LTX-2.git cd LTX-2 uv sync --frozen
# Download the weights from this repo, plus the Gemma text encoder hf download suryatmodulus/scena --local-dir models/scena hf download google/gemma-3-12b-it-qat-q4_0-unquantized --local-dir models/gemma-3-12b
# Fast pipeline (distilled model, no distilled LoRA needed) uv run python -m ltx_pipelines.distilled \ --distilled-checkpoint-path models/scena/<distilled-checkpoint>.safetensors \ --spatial-upsampler-path models/scena/<spatial-upsampler>.safetensors \ --gemma-root models/gemma-3-12b \ --prompt "A beautiful sunset over the ocean" \ --output-path output.mp4 # For image-to-video, add: --image path/to/image.jpg 0 0.8# HQ pipeline (two-stage, higher quality) uv run python -m ltx_pipelines.ti2vid_two_stages_hq \ --checkpoint-path models/scena/<checkpoint>.safetensors \ --distilled-lora models/scena/<distilled-lora>.safetensors 0.8 \ --spatial-upsampler-path models/scena/<spatial-upsampler>.safetensors \ --gemma-root models/gemma-3-12b \ --prompt "A beautiful sunset over the ocean" \ --output-path output.mp4 # For image-to-video, add: --image path/to/image.jpg 0 0.8 - Notebooks
- Google Colab
- Kaggle
Commit ·
ce8b1cd
0
Parent(s):
Duplicate from mifinkelson/scena
Browse filesCo-authored-by: Michael Finkelson <mifinkelson@users.noreply.huggingface.co>
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- scena.safetensors +3 -0
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README.md
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---
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license: other
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license_name: ltx-2-community-license
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license_link: https://huggingface.co/Lightricks/LTX-2/blob/main/LICENSE
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language:
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- en
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tags:
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- audio
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- text-to-audio
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- audio-generation
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- speech
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- reference-conditioning
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- multi-speaker
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- flow-matching
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- diffusion
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- ltx
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library_name: ltx-audio
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pipeline_tag: text-to-audio
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---
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# ScenA — Reference-Driven Multi-Speaker Audio Scene Generation
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**ScenA** generates multi-speaker audio *scenes* (dialogue, conversation) from a text
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prompt, conditioned on one or more **reference-audio** clips that set the speakers'
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voices. It is an audio-only, reference-conditioned text-to-audio flow-matching DiT
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built on the LTX-2 architecture (~4B parameters, 48 layers).
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- 📄 **Paper:** [arXiv:2606.19325](https://arxiv.org/abs/2606.19325)
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- 🌐 **Project page:** https://finmickey.github.io/scena/
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- 💻 **Code:** https://github.com/finmickey/scena
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- 🏢 Lightricks · Tel Aviv University
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## Files
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| file | size | contents |
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|---|---|---|
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| `scena.safetensors` | ~8.2 GB | the ScenA transformer + Gemma text-projection weights |
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| `audio_vae.safetensors` | ~365 MB | the audio VAE (encoder+decoder) + vocoder (bundled so you don't need the full LTX-2 model) |
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You also need the **Gemma-3-12B-IT** text encoder (`google/gemma-3-12b-it`, gated on HF).
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## Quickstart
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```bash
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git clone https://github.com/finmickey/scena
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cd scena
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pip install -e . # or: uv sync
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# download the checkpoint + audio VAE bundle
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huggingface-cli download mifinkelson/scena scena.safetensors audio_vae.safetensors --local-dir ./checkpoints
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```
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Two example reference voices ship with the repo under `examples/references/` — the same two voices
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drive both examples below, so this runs out of the box:
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```python
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from ltx_pipelines.t2aud_ref_cond import T2AudRefCondPipeline
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pipe = T2AudRefCondPipeline(
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checkpoint_path="checkpoints/scena.safetensors",
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audio_vae_path="checkpoints/audio_vae.safetensors",
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gemma_root="/path/to/google/gemma-3-12b-it",
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)
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refs = ["examples/references/reference_1.wav", "examples/references/reference_2.wav"]
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# A simple two-speaker dialogue
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pipe(
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prompt='The speaker from reference 1 says: "The taxi drivers are on strike again." The speaker from reference 2 says: "What for?" The speaker from reference 1 says: "They want the government to reduce the price of the gasoline." The speaker from reference 2 says: "It is really a hot potato."',
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ref_audio_paths=refs,
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duration=7.0,
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seed=1,
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).save("dialogue.wav")
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# Farm at sunrise — the same two voices in a scene with sound effects
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pipe(
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prompt='A farm at sunrise: a rooster crows. Chickens cluck softly throughout. The speaker from reference 1 says with a yawn: "Way too early for this." The speaker from reference 2 chuckles: "Welcome to country life." The rooster crows again.',
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ref_audio_paths=refs,
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duration=8.0,
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seed=1,
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).save("farm.wav")
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```
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### Prompting guide
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- Refer to speakers as **"the speaker from reference 1"**, **"reference 2"**, … matching the
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order of `ref_audio_paths`.
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- Put the spoken words **in quotes**; describe sound effects / ambience in plain prose
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(e.g. *"rain drums steadily on a tin roof"*, *"a roaring stadium crowd cheers"*).
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- Reference clips: clean single-speaker speech, up to ~20 s each — the more the better (any sample rate; mono or stereo).
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- You don't have to follow a strict turn-taking pattern; see the [demo page](https://finmickey.github.io/scena/) for more varied examples.
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- 60 inference steps, guidance ~7, and output durations up to ~20 s work best (the model was trained on ≤20 s scenes).
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## Citation
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```bibtex
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@article{finkelson2026scena,
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title = {Reference-Driven Multi-Speaker Audio Scene Generation from In-the-Wild Priors},
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author = {Finkelson, Michael and Segal, Daniel and Richardson, Eitan and Armon, Shahar and Goldring, Nani and Panet, Poriya and Zabari, Nir and Brazowski, Benjamin and Patashnik, Or and HaCohen, Yoav},
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journal = {arXiv preprint arXiv:2606.19325},
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year = {2026}
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}
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```
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## License
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Released under the [LTX-2 Community License](https://huggingface.co/Lightricks/LTX-2/blob/main/LICENSE).
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version https://git-lfs.github.com/spec/v1
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oid sha256:b1f536f192420e1abd936b5ff10ea0ef7204058db2e1e79a865ab36e06b29847
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size 364831364
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scena.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:3cb54ca58aa61eae5823cca01563463dd096b8fa39352f9a02f7232dfabadd35
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size 8153188488
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