Automatic Speech Recognition
Transformers
Safetensors
PyTorch
arkasr
text-generation
speech
audio
multilingual
hotword
audio8
custom_code
Eval Results
Instructions to use Edge0/Audio8-ASR-0.1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Edge0/Audio8-ASR-0.1B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Edge0/Audio8-ASR-0.1B", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Edge0/Audio8-ASR-0.1B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
docs: add German and Korean support
Browse files
README.md
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license: apache-2.0
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repository: https://github.com/AutoArk/open-audio-opd
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`Audio8-ASR-0.1B` is a compact autoregressive ASR model whose language-model
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component has only 0.1B parameters. It supports multilingual speech recognition
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for languages including Chinese, English, French, Japanese,
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position it as one of the smallest usable performance ASR models
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This base repository provides the Hugging Face Transformers checkpoint. We also
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provide deployment-focused releases:
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- fr
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- ja
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- yue
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- de
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- ko
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license: apache-2.0
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repository: https://github.com/AutoArk/open-audio-opd
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---
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`Audio8-ASR-0.1B` is a compact autoregressive ASR model whose language-model
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component has only 0.1B parameters. It supports multilingual speech recognition
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for languages including Chinese, English, French, German, Japanese, Korean, and
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Cantonese. We position it as one of the smallest usable performance ASR models
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in the LLM era.
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This base repository provides the Hugging Face Transformers checkpoint. We also
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provide deployment-focused releases:
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