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meghanamakkapati
/
MistralAI_INT4_quantization

Automatic Speech Recognition
Transformers
Safetensors
voxtral_realtime
mistral
voxtral
voxtral-realtime
asr
quantization
bitsandbytes
int4
nf4
4-bit precision
Model card Files Files and versions
xet
Community

Instructions to use meghanamakkapati/MistralAI_INT4_quantization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use meghanamakkapati/MistralAI_INT4_quantization with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("automatic-speech-recognition", model="meghanamakkapati/MistralAI_INT4_quantization")
    # Load model directly
    from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
    
    processor = AutoProcessor.from_pretrained("meghanamakkapati/MistralAI_INT4_quantization")
    model = AutoModelForSpeechSeq2Seq.from_pretrained("meghanamakkapati/MistralAI_INT4_quantization")
  • Notebooks
  • Google Colab
  • Kaggle
MistralAI_INT4_quantization
2.92 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
meghanamakkapati's picture
meghanamakkapati
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0022f1c verified about 21 hours ago
  • .gitattributes
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  • README.md
    2.21 kB
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  • config.json
    2.07 kB
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  • generation_config.json
    191 Bytes
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  • model.safetensors
    2.91 GB
    xet
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  • processor_config.json
    384 Bytes
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  • tekken.json
    14.9 MB
    xet
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  • vllm_config.yaml
    226 Bytes
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