Audio Classification
Transformers
Safetensors
multilingual
wav2vec2-dual-hypersphere
audio-deepfake
deepfake-detection
deepfake
voice-cloning
anti-spoofing
asvspoof
wav2vec2
speech
audio
synthetic-voice
voice-conversion
tts-detection
trust-and-safety
security
SoTA
Modotte
custom_code
Instructions to use Modotte/AIRealNet-Audio with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Modotte/AIRealNet-Audio with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Modotte/AIRealNet-Audio", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForAudioClassification model = AutoModelForAudioClassification.from_pretrained("Modotte/AIRealNet-Audio", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from Modotte/AIRealNet-Audio: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/Modotte/AIRealNet-Audio/resolve/main/model.safetensors
- Command line
-
hf download hf://Modotte/AIRealNet-Audio/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Modotte/AIRealNet-Audio/resolve/main/model.safetensors
378 MB
- Xet hash:
- 510d570b0fc330742143d31f1afa67e11fbceae291b9b1793ddeeb4f246789db
- Size of remote file:
- 378 MB
- SHA256:
- 219378a69e2a2f590676f89a2ce73f9ed8c12d0c3e2ab41db8884598c0be633b
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