Instructions to use zenlm/zen-foley with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zenlm/zen-foley with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-to-audio", model="zenlm/zen-foley")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("zenlm/zen-foley", dtype="auto") - Notebooks
- Google Colab
- Kaggle
Zen Foley
Foley sound effects generation model for video and interactive media production.
Overview
Built on Zen MoDE (Mixture of Distilled Experts) architecture with 1B parameters.
Developed by Hanzo AI and the Zoo Labs Foundation.
Quick Start
from transformers import AutoModelForSpeechSeq2Seq, AutoProcessor
import torch
model_id = "zenlm/zen-foley"
processor = AutoProcessor.from_pretrained(model_id)
model = AutoModelForSpeechSeq2Seq.from_pretrained(model_id, torch_dtype=torch.float16, device_map="auto")
# Load audio
import librosa
audio, sr = librosa.load("audio.wav", sr=16000)
inputs = processor(audio, sampling_rate=sr, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs)
print(processor.batch_decode(outputs, skip_special_tokens=True)[0])
Model Details
| Attribute | Value |
|---|---|
| Parameters | 1B |
| Architecture | Zen MoDE |
| Context | 10s audio |
| License | Apache 2.0 |
License
Apache 2.0
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