Automatic Speech Recognition
Transformers
Safetensors
Danish
cohere_asr
audio
speech-recognition
transcription
danish
hf-asr-leaderboard
custom_code
Instructions to use syvai/hviske-v5.3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use syvai/hviske-v5.3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="syvai/hviske-v5.3", trust_remote_code=True)# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("syvai/hviske-v5.3", trust_remote_code=True) model = AutoModelForSpeechSeq2Seq.from_pretrained("syvai/hviske-v5.3", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload hviske-v5.3: LLRD mult=0.75, 5 epochs — full-test avg WER 15.56% (read_aloud 10.26%, conv 21.30%)
17aa942 verified - Xet hash:
- e34e35dd62b803ba5362bcb26d30b654afacacf369f632dc5908df59a4046152
- Size of remote file:
- 493 kB
- SHA256:
- 6d21e6a83b2d0d3e1241a7817e4bef8eb63bcb7cfe4a2675af9a35ff3bbf0e14
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