Automatic Speech Recognition
Transformers
Safetensors
English
wav2vec2
speech
asr
audio-regression
multitask-learning
whisper
gradio
sagemaker
custom_code
Instructions to use Amirhossein75/speech-intensity-wav2vec with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Amirhossein75/speech-intensity-wav2vec with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Amirhossein75/speech-intensity-wav2vec", trust_remote_code=True)# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Amirhossein75/speech-intensity-wav2vec", trust_remote_code=True) model = AutoModelForCTC.from_pretrained("Amirhossein75/speech-intensity-wav2vec", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- bcbab1e50ffc6e4a38e81c4153b18e7aefd248c5b1a91c67b259ac1b5b30fa5d
- Size of remote file:
- 5.71 kB
- SHA256:
- 6d7726847e7ccdd715b19f6fae3056bdc8260549f86474484d248113008486b4
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