Instructions to use mispeech/r1-aqa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mispeech/r1-aqa with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("mispeech/r1-aqa") model = AutoModelForMultimodalLM.from_pretrained("mispeech/r1-aqa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
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Add descriptive tags to model card
Verified signatureThis PR improves the model card by adding more descriptive tags to the metadata, such as `audio-question-answering`, `reinforcement-learning`, and `multimodal-llm`. These tags will help users discover the model more easily when searching on the Hub. All existing content and links (to GitHub and the technical report on arXiv) remain unchanged as they are already accurate and complete for this model.5f4044d
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Update README.md (#11)
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Add audio-text-to-text pipeline tag (#3)
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Update README.md (#2)
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Upload processor
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Upload Qwen2AudioForConditionalGeneration
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initial commit
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