Instructions to use KoshiMazaki/akuspace-ltx25 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LTX.io
How to use KoshiMazaki/akuspace-ltx25 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 KoshiMazaki/akuspace-ltx25 --local-dir models/akuspace-ltx25 hf download google/gemma-3-12b-it-qat-q4_0-unquantized --local-dir models/gemma-3-12b
# Text/image-to-video with the LoRA on the HQ two-stage base pipeline uv run python -m ltx_pipelines.ti2vid_two_stages_hq \ --checkpoint-path path/to/checkpoint.safetensors \ --distilled-lora path/to/distilled_lora.safetensors 0.8 \ --spatial-upsampler-path path/to/spatial_upsampler.safetensors \ --gemma-root models/gemma-3-12b \ --lora models/akuspace-ltx25/<weights>.safetensors 1.0 \ --prompt "your prompt here" \ --output-path output.mp4 # For image-to-video, add: --image path/to/image.jpg 0 0.8 - Reverb
How to use KoshiMazaki/akuspace-ltx25 with Reverb:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
| """Envelope cross-correlation between a dry reference and its a2a render. | |
| Reproduces the timing measurement published in the AKUSPACE model card, so new | |
| examples can be added to that table on the same basis rather than asserted. | |
| Method: amplitude envelope of each signal in 2 ms RMS windows, mean-removed and | |
| normalised, cross-correlated over +/-250 ms. Reports the offset of peak | |
| correlation and the peak value. | |
| Reading the result: peak r measures how much the envelope CHANGED, and reverb | |
| changes it by design — most on transient-dense material, where the tail fills | |
| the gaps between hits. A low r on percussion is the effect working, not drift. | |
| The offset is the timing claim; r is not a quality score. | |
| """ | |
| import argparse | |
| import subprocess | |
| import sys | |
| import wave | |
| from pathlib import Path | |
| import numpy as np | |
| WIN_MS = 2.0 | |
| MAX_LAG_MS = 250.0 | |
| def load_mono(path: Path, sr: int = 48000) -> np.ndarray: | |
| """Decode anything ffmpeg reads into mono float at sr.""" | |
| out = subprocess.run( | |
| ["ffmpeg", "-v", "error", "-i", str(path), "-ac", "1", "-ar", str(sr), | |
| "-f", "wav", "-c:a", "pcm_s16le", "-"], | |
| capture_output=True, check=True).stdout | |
| import io | |
| with wave.open(io.BytesIO(out), "rb") as w: | |
| raw = w.readframes(w.getnframes()) | |
| return np.frombuffer(raw, dtype="<i2").astype(np.float64) / 32768.0 | |
| def envelope(x: np.ndarray, sr: int) -> np.ndarray: | |
| n = max(1, int(sr * WIN_MS / 1000.0)) | |
| trimmed = x[: len(x) - len(x) % n] | |
| return np.sqrt((trimmed.reshape(-1, n) ** 2).mean(axis=1) + 1e-12) | |
| def xcorr(a: np.ndarray, b: np.ndarray, max_lag: int) -> tuple[int, float]: | |
| n = min(len(a), len(b)) | |
| a, b = a[:n], b[:n] | |
| a = (a - a.mean()) / (a.std() or 1e-12) | |
| b = (b - b.mean()) / (b.std() or 1e-12) | |
| best_lag, best_r = 0, -2.0 | |
| for lag in range(-max_lag, max_lag + 1): | |
| if lag < 0: | |
| x, y = a[-lag:], b[: n + lag] | |
| elif lag > 0: | |
| x, y = a[: n - lag], b[lag:] | |
| else: | |
| x, y = a, b | |
| if len(x) < 10: | |
| continue | |
| r = float((x * y).mean()) | |
| if r > best_r: | |
| best_r, best_lag = r, lag | |
| return best_lag, best_r | |
| def main() -> int: | |
| p = argparse.ArgumentParser(description=__doc__, formatter_class=argparse.RawDescriptionHelpFormatter) | |
| p.add_argument("--dry", required=True) | |
| p.add_argument("--wet", nargs="+", required=True) | |
| p.add_argument("--sr", type=int, default=48000) | |
| a = p.parse_args() | |
| dry = envelope(load_mono(Path(a.dry), a.sr), a.sr) | |
| max_lag = int(MAX_LAG_MS / WIN_MS) | |
| print(f"{'example':38s} {'offset':>9s} {'peak r':>8s}") | |
| for w in a.wet: | |
| wet = envelope(load_mono(Path(w), a.sr), a.sr) | |
| lag, r = xcorr(dry, wet, max_lag) | |
| # positive lag = wet later than dry; report with the card's sign convention | |
| print(f"{Path(w).stem:38s} {lag * WIN_MS:+8.0f}ms {r:8.2f}") | |
| return 0 | |
| if __name__ == "__main__": | |
| sys.exit(main()) | |