How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("automatic-speech-recognition", model="GlowLED/whisper-tiny-minds14-en")
# pip install -U transformers accelerate
# Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq

processor = AutoProcessor.from_pretrained("GlowLED/whisper-tiny-minds14-en")
model = AutoModelForSpeechSeq2Seq.from_pretrained("GlowLED/whisper-tiny-minds14-en", device_map="auto")
Quick Links

whisper-tiny-minds14-en

Fine-tuned openai/whisper-tiny on PolyAI/minds14 en-US (first 450 examples as train). Normalised WER 0.2341 (< 0.37). Use with WhisperForConditionalGeneration + WhisperProcessor.

Metrics

  • wer: 0.2341

Usage

# automatic-speech-recognition
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Model size
37.8M params
Tensor type
F32
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