Instructions to use emonidi/order-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use emonidi/order-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="emonidi/order-tiny")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("emonidi/order-tiny") model = AutoModelForSpeechSeq2Seq.from_pretrained("emonidi/order-tiny") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8be11c345b1e5fafb96779ad853e190abec4804dc25b79ba9ef98bc68085d30f
- Size of remote file:
- 151 MB
- SHA256:
- 41fbeb9f6f5187897648a55ddc2474d3bbb190ddada88bf77635f74ae5f52654
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