Automatic Speech Recognition
Transformers
Safetensors
Chinese
English
ming_v3_asr
text-generation
audio
speech-recognition
contextual-asr
custom_code
Instructions to use ArchiveStudio/Ming-3.0-asr-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArchiveStudio/Ming-3.0-asr-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ArchiveStudio/Ming-3.0-asr-tiny", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("ArchiveStudio/Ming-3.0-asr-tiny", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 329 Bytes
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message: "If you use Ming-3.0-asr-tiny, please cite this model repository."
title: "Ming-3.0-asr-tiny: Context-Aware Speech Recognition"
type: software
authors:
- name: inclusionAI
license: MIT
url: "https://github.com/inclusionAI/Ming-3.0-asr"
repository-code: "https://github.com/inclusionAI/Ming-3.0-asr"
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