Automatic Speech Recognition
Transformers
PyTorch
whisper
audio
speech
wav2vec2
Eval Results (legacy)
Instructions to use devasheeshG/whisper_medium_fp16_transformers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use devasheeshG/whisper_medium_fp16_transformers with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="devasheeshG/whisper_medium_fp16_transformers")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("devasheeshG/whisper_medium_fp16_transformers") model = AutoModelForSpeechSeq2Seq.from_pretrained("devasheeshG/whisper_medium_fp16_transformers", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): f248fdd
Update README.md
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README.md
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A file ``__init__.py`` is contained inside this repo which contains all the code to use this model.
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Firstly, clone this repo and place all the files inside a folder.
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**Please try in jupyter notebook**
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```python
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A file ``__init__.py`` is contained inside this repo which contains all the code to use this model.
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Firstly, clone this repo and place all the files inside a folder.
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# Make sure you have git-lfs installed (https://git-lfs.com)
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```bash
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git lfs install
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git clone https://huggingface.co/devasheeshG/whisper_medium_fp16_transformers
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```
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**Please try in jupyter notebook**
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```python
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