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ghecko78
/
Voxtral-Mini-4B-Realtime-2602-FP8-Dynamic

Automatic Speech Recognition
Transformers
Safetensors
voxtral_realtime
fp8
quantized
vllm
mistral
compressed-tensors
llm-compressor
Model card Files Files and versions
xet
Community
1

Instructions to use ghecko78/Voxtral-Mini-4B-Realtime-2602-FP8-Dynamic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use ghecko78/Voxtral-Mini-4B-Realtime-2602-FP8-Dynamic with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="ghecko78/Voxtral-Mini-4B-Realtime-2602-FP8-Dynamic")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("ghecko78/Voxtral-Mini-4B-Realtime-2602-FP8-Dynamic")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("ghecko78/Voxtral-Mini-4B-Realtime-2602-FP8-Dynamic")
  • Notebooks
  • Google Colab
  • Kaggle
Voxtral-Mini-4B-Realtime-2602-FP8-Dynamic
5.84 GB
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  • 1 contributor
History: 7 commits
ghecko78's picture
ghecko78
Upload FP8-quantized model (FP8_DYNAMIC, via llm-compressor)
35e3d04 verified 12 days ago
  • .gitattributes
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  • README.md
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  • config.json
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  • generation_config.json
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  • model.safetensors
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  • processor_config.json
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  • recipe.yaml
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    Upload FP8-quantized model (FP8_DYNAMIC, via llm-compressor) about 2 months ago
  • tekken.json
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