Instructions to use defining/maggle with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use defining/maggle with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="defining/maggle")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("defining/maggle") model = AutoModelForSpeechSeq2Seq.from_pretrained("defining/maggle") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:57a1ba2a82c093cabff2541409ae778c97145378b9ddfa722763cb1cb8f9020b
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size 6173370152
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