Instructions to use hf-internal-testing/tiny-random-wav2vec2-adapter with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-wav2vec2-adapter with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hf-internal-testing/tiny-random-wav2vec2-adapter")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-wav2vec2-adapter") model = AutoModelForCTC.from_pretrained("hf-internal-testing/tiny-random-wav2vec2-adapter", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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[Awaiting approval] Upload ONNX weights
Verified signature[Automated] Converted using [Optimum](https://github.com/huggingface/optimum). Models will be merged manually by @Xenova once they have been checked with [Transformers.js](https://github.com/xenova/transformers.js).f5153f0
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[MMS] Fix mms
34f454b
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add dummy weight
c799d13
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up
7484300
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upload all adapters
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Duplicate from hf-internal-testing/tiny-random-wav2vec2
Co-authored-by: Julien Chaumond <julien-c@users.noreply.huggingface.co>181a462