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
Download tokenizer.json from mispeech/r1-aqa: direct link, hf CLI and curl.
- Browser
- Download file 12 MB
-
https://huggingface.co/mispeech/r1-aqa/resolve/refs%2Fpr%2F8/tokenizer.json
- Command line
-
hf download hf://mispeech/r1-aqa@refs/pr/8/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/mispeech/r1-aqa/resolve/refs%2Fpr%2F8/tokenizer.json
12 MB
- Xet hash:
- f1727e700199f801c8b4155e3d778ab6d9e95a5cbb1a9c191a74f1db2428f39b
- Size of remote file:
- 12 MB
- SHA256:
- 1d466fd119821fa5ac2d8d99b740b042bcde55dd564c575a514cd82fc56dddb6
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