Automatic Speech Recognition
Transformers
Safetensors
English
asr_model
feature-extraction
asr
speech-recognition
audio
qwen
glm-asr
custom_code
Instructions to use mazesmazes/tiny-audio with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mazesmazes/tiny-audio with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mazesmazes/tiny-audio", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mazesmazes/tiny-audio", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Revert to 5a38762f (end of stage 1) — drop second stage 2 attempt
Browse filesSecond stage-2 attempt was launched with the milder aug recipe but still at the original peak LRs (lr=1e-3, decoder_lr=1e-4), which is too high for resumed-from-converged training. Lowering peak LRs (lr=3e-4, decoder_lr=3e-5) and restarting from the stage-1 baseline.
- model.safetensors +1 -1
- training_args.bin +1 -1
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