Instructions to use smcproject/Malwhisper-v1-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use smcproject/Malwhisper-v1-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="smcproject/Malwhisper-v1-small")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("smcproject/Malwhisper-v1-small") model = AutoModelForSpeechSeq2Seq.from_pretrained("smcproject/Malwhisper-v1-small") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model (#1)
Browse files- Adding `safetensors` variant of this model (b70bdba36a136adc72a37cdd602cbd557fda4be8)
Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:79de5988947e0a9b8b030ad19c80e1a49179e22a5f4510bea9170b8d33cec2fe
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size 966995136
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