Automatic Speech Recognition
PEFT
Safetensors
English
whisper
lora
audio
machine-sound
anomaly-detection
predictive-maintenance
manufacturing
voice-agent
text-to-speech
non-commercial
Eval Results (legacy)
Instructions to use muruganmath/Machine-fault-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use muruganmath/Machine-fault-detector with PEFT:
from peft import PeftModel from transformers import AutoModelForSpeechSeq2Seq base_model = AutoModelForSpeechSeq2Seq.from_pretrained("openai/whisper-large-v3") model = PeftModel.from_pretrained(base_model, "muruganmath/Machine-fault-detector") - Notebooks
- Google Colab
- Kaggle
Add trained LoRA adapter (main), tokenizer/processor, lineage, standalone inference and model card
36ba721 verified Download tokenizer.json from muruganmath/Machine-fault-detector: direct link, hf CLI and curl.
- Browser
- Download file 3.93 MB
-
https://huggingface.co/muruganmath/Machine-fault-detector/resolve/main/tokenizer.json
- Command line
-
hf download hf://muruganmath/Machine-fault-detector/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/muruganmath/Machine-fault-detector/resolve/main/tokenizer.json
3.93 MB
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