How to use Siphh/wabLab2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Siphh/wabLab2")
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Siphh/wabLab2") model = AutoModelForSpeechSeq2Seq.from_pretrained("Siphh/wabLab2", device_map="auto")
https://huggingface.co/Siphh/wabLab2/resolve/main/README.md
hf download hf://Siphh/wabLab2/README.md
curl -L -o README.md https://huggingface.co/Siphh/wabLab2/resolve/main/README.md
license: apache-2.0 datasets: - mozilla-foundation/common_voice_11_0 language: - sv metrics: - wer
