Instructions to use smcproject/Malwhisper-v1-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use smcproject/Malwhisper-v1-medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="smcproject/Malwhisper-v1-medium")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("smcproject/Malwhisper-v1-medium") model = AutoModelForSpeechSeq2Seq.from_pretrained("smcproject/Malwhisper-v1-medium", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b427b886a2fe0e306b1d9569709f9843f443a54d37a589460c3dc99d90e83b83
- Size of remote file:
- 4.86 kB
- SHA256:
- a646bb1961f8def634c98eac293516d3c2e4d8302db7a67a8c5d20942e9a4ede
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