Instructions to use Thamer/wav2vec-fine_tuned-speech_command2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Thamer/wav2vec-fine_tuned-speech_command2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Thamer/wav2vec-fine_tuned-speech_command2")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("Thamer/wav2vec-fine_tuned-speech_command2") model = AutoModelForAudioClassification.from_pretrained("Thamer/wav2vec-fine_tuned-speech_command2") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:f9bcce7cb95f96ea082c2dbdbba623ac269b2953f0f3f3f496abf0b069954c1b
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size 378332132
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