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Copperside/CoppersideASR

sourceHugging Facemitupdated 4mo agoView on Hugging Face
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Model Card

CoppersideASR

CoppersideASR is an ONNX RNN-T speech recognition model bundle for the CopperASR runtime. The model is configured for Russian speech recognition and 16 kHz audio input.

The repository uses a minimal normalized layout: three ONNX graphs, a token mapping, and a runtime manifest. CopperASR can load this bundle directly without additional conversion steps.

Files

  • —encoder.onnx
  • —decoder.onnx
  • —joint.onnx
  • —tokens.txt
  • —model_manifest.json

Runtime Contract

FilePurpose
encoder.onnxRNN-T acoustic encoder
decoder.onnxRNN-T prediction network
joint.onnxRNN-T joint network
tokens.txtToken id mapping with <blk> at id 1024
model_manifest.jsonRuntime contract and checksums

Usage with CopperASR

python
from copper_asr import CopperASR

asr = CopperASR(model_source="copperside-gigaam-v3-e2e-rnnt")
result = asr.transcribe("audio.wav")
print(result.full_text)

For a local checkout:

python
asr = CopperASR(
    model_source="copperside-gigaam-v3-e2e-rnnt",
    model_path="path/to/CoppersideASR",
)

Model Details

The model uses an RNN-T layout with separate encoder, decoder, and joint ONNX graphs. Tokenizer settings, feature extraction parameters, decoder limits, and file checksums are recorded in model_manifest.json.