Automatic Speech Recognition
Transformers
TensorBoard
ONNX
Safetensors
whisper
Generated from Trainer
Instructions to use antonvinny/whisper-tiny-anton with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use antonvinny/whisper-tiny-anton with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="antonvinny/whisper-tiny-anton")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("antonvinny/whisper-tiny-anton") model = AutoModelForSpeechSeq2Seq.from_pretrained("antonvinny/whisper-tiny-anton", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload tokenizer_config.json with huggingface_hub
Browse files- tokenizer_config.json +0 -1
tokenizer_config.json
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"clean_up_tokenization_spaces": true,
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"eos_token": "<|endoftext|>",
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"errors": "replace",
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"extra_special_tokens": {},
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"model_max_length": 1024,
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"pad_token": "<|endoftext|>",
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"processor_class": "WhisperProcessor",
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"clean_up_tokenization_spaces": true,
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"eos_token": "<|endoftext|>",
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"errors": "replace",
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"model_max_length": 1024,
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"pad_token": "<|endoftext|>",
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"processor_class": "WhisperProcessor",
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