Automatic Speech Recognition
Transformers
Safetensors
PyTorch
arkasr
text-generation
speech
audio
vllm
ark-asr
custom_code
Eval Results
Instructions to use AutoArk-AI/ARK-ASR-3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AutoArk-AI/ARK-ASR-3B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="AutoArk-AI/ARK-ASR-3B", trust_remote_code=True, device_map="auto")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("AutoArk-AI/ARK-ASR-3B", trust_remote_code=True, dtype="auto", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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## Evaluation
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```bash
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python scripts/eval/eval_jwer_ark_asr_transformers.py \
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## Evaluation
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The reported leaderboard numbers are evaluated with the Hugging Face
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[`open_asr_leaderboard`](https://github.com/huggingface/open_asr_leaderboard)
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evaluation code.
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For local J/WER evaluation, the repository also includes this entrypoint:
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```bash
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python scripts/eval/eval_jwer_ark_asr_transformers.py \
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