Automatic Speech Recognition
Transformers
PyTorch
Divehi
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use 64FC/whisper-small-dv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use 64FC/whisper-small-dv with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="64FC/whisper-small-dv")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("64FC/whisper-small-dv") model = AutoModelForSpeechSeq2Seq.from_pretrained("64FC/whisper-small-dv", device_map="auto") - 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:d646cf3e3e2b5a1783789b47fc56c29e63b249a2a7ff7981dbee2014c4340293
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size 966995136
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