Instructions to use zeromodels/whisper_tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasFormers
How to use zeromodels/whisper_tiny with KerasFormers:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Keras
How to use zeromodels/whisper_tiny with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://zeromodels/whisper_tiny") - Notebooks
- Google Colab
- Kaggle
Update class name in the quick start
Browse files
README.md
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@@ -32,7 +32,7 @@ For more details on the model, please go to the upstream [model card](https://hu
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Pure-**Keras 3** conversion of [`openai/whisper-tiny`](https://huggingface.co/openai/whisper-tiny) for [kerasformers](https://github.com/IMvision12/KerasFormers). One implementation runs unmodified on **TensorFlow / Torch / JAX**.
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This is an **ASR** checkpoint (`
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## ✨ Quick start
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import soundfile as sf
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from kerasformers.models.whisper import (
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WhisperProcessor,
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)
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model =
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processor = WhisperProcessor.from_weights("kerasformers/whisper_tiny")
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audio, sr = sf.read("your_audio.wav", dtype="float32") # 16 kHz mono
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- Prefer `WhisperProcessor.from_weights(...)` so mel bins match the variant (v3 uses 128).
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- Clips are padded to a 30 s window; chunk longer audio yourself.
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- See [Whisper docs](https://imvision12.github.io/KerasFormers/whisper/) and [Loading Weights](https://imvision12.github.io/KerasFormers/loading_weights/).
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- Community / upstream safetensors still work via the `hf:` prefix, e.g. `
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## Special Thanks
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Pure-**Keras 3** conversion of [`openai/whisper-tiny`](https://huggingface.co/openai/whisper-tiny) for [kerasformers](https://github.com/IMvision12/KerasFormers). One implementation runs unmodified on **TensorFlow / Torch / JAX**.
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This is an **ASR** checkpoint (`WhisperConditionalGenerate`, 39M).
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## ✨ Quick start
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import soundfile as sf
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from kerasformers.models.whisper import (
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WhisperProcessor,
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WhisperConditionalGenerate,
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)
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model = WhisperConditionalGenerate.from_weights("kerasformers/whisper_tiny")
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processor = WhisperProcessor.from_weights("kerasformers/whisper_tiny")
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audio, sr = sf.read("your_audio.wav", dtype="float32") # 16 kHz mono
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- Prefer `WhisperProcessor.from_weights(...)` so mel bins match the variant (v3 uses 128).
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- Clips are padded to a 30 s window; chunk longer audio yourself.
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- See [Whisper docs](https://imvision12.github.io/KerasFormers/whisper/) and [Loading Weights](https://imvision12.github.io/KerasFormers/loading_weights/).
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- Community / upstream safetensors still work via the `hf:` prefix, e.g. `WhisperConditionalGenerate.from_weights("hf:openai/whisper-tiny")`.
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## Special Thanks
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