Instructions to use Shubham09/whisper_tflite with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Shubham09/whisper_tflite with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Shubham09/whisper_tflite")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Shubham09/whisper_tflite") model = AutoModelForSpeechSeq2Seq.from_pretrained("Shubham09/whisper_tflite", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload whisper_f16_small.tflite
Browse files- whisper_f16_small.tflite +3 -0
whisper_f16_small.tflite
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version https://git-lfs.github.com/spec/v1
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oid sha256:b89dc3f1293abeff7e016377f08c5edc5d5cd0c25b50a78e90a04f0c0e8b377a
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size 485352164
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