Automatic Speech Recognition
Transformers
ONNX
Safetensors
Armenian
whisper
asr
audio
speech
low-resource
morpheme-tokenization
armenian
compact-model
Generated from Trainer
Eval Results (legacy)
Instructions to use Chillarmo/ATOM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Chillarmo/ATOM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Chillarmo/ATOM")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Chillarmo/ATOM") model = AutoModelForSpeechSeq2Seq.from_pretrained("Chillarmo/ATOM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download optimizer.pt from Chillarmo/ATOM: direct link, hf CLI and curl.
- Browser
- Download file 48.3 MB
-
https://huggingface.co/Chillarmo/ATOM/resolve/refs%2Fpr%2F1/optimizer.pt
- Command line
-
hf download hf://Chillarmo/ATOM@refs/pr/1/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Chillarmo/ATOM/resolve/refs%2Fpr%2F1/optimizer.pt
48.3 MB
- Xet hash:
- d313cdb076e9dca4f424e5d5d1f436f53391d40440b959f88f3c0b86bcf49bf7
- Size of remote file:
- 48.3 MB
- SHA256:
- 522cb173c1edaed339d0d2a44d3d383f4981a84159179948b3cad975dccebc86
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