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WannaGoTech
/
WannaMedASR

Automatic Speech Recognition
Transformers
French
English
Arabic
medical
radiology
clinical-dictation
french
healthcare
snomed-ct
wannamed
wannagotech
Eval Results (legacy)
Model card Files Files and versions
xet
Community

Instructions to use WannaGoTech/WannaMedASR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use WannaGoTech/WannaMedASR with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="WannaGoTech/WannaMedASR")
    # pip install -U transformers accelerate
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("WannaGoTech/WannaMedASR", device_map="auto")
  • Notebooks
  • Google Colab
  • Kaggle
WannaMedASR
11.3 MB
Ctrl+K
Ctrl+K
  • 2 contributors
History: 30 commits
WannaGoTech-TN's picture
WannaGoTech-TN
Update WannaGoTech_Ecosystem_Cover.png with the 5-model WannaMed ecosystem
82e09f4 verified 3 days ago
  • assets
    WannaMedASR v2 (0.48% CER • 99.52% Precision • 0.82% WER) — Official Release Assets 4 days ago
  • brand
    Update WannaGoTech_Ecosystem_Cover.png with the 5-model WannaMed ecosystem 3 days ago
  • screenshots
    Fix official colored WannaMed & WannaGoTech header SVG and keep only dictation bar screenshot 5 days ago
  • .gitattributes
    2.46 kB
    Deploy new HTML/SVG Retina covers, sovereign naming (0 base model mention) & 6-section card 3 days ago
  • README.md
    20.7 kB
    Deploy new HTML/SVG Retina covers, sovereign naming (0 base model mention) & 6-section card 3 days ago
  • official_benchmark_comparison.json
    2.45 kB
    Deploy new HTML/SVG Retina covers, sovereign naming (0 base model mention) & 6-section card 3 days ago
  • training_metrics.json
    2.22 kB
    Deploy new HTML/SVG Retina covers, sovereign naming (0 base model mention) & 6-section card 3 days ago
  • wannamed_benchmark_report.json
    1.22 kB
    WannaMedASR v2 (0.48% CER / 0.82% WER - 99.52% Precision): Official Hold-Out Benchmark and Methodology 4 days ago
  • wannamed_lora_fused.json
    924 Bytes
    Update wannamed_lora_fused.json (wannamed_tx_enabled_in_prod) 3 days ago