Instructions to use Raffay/local_speech_processing_project_wav2vec2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Raffay/local_speech_processing_project_wav2vec2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Raffay/local_speech_processing_project_wav2vec2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("Raffay/local_speech_processing_project_wav2vec2") model = AutoModelForCTC.from_pretrained("Raffay/local_speech_processing_project_wav2vec2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from Raffay/local_speech_processing_project_wav2vec2: direct link, hf CLI and curl.
- Browser
- Download file 85 Bytes
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https://huggingface.co/Raffay/local_speech_processing_project_wav2vec2/resolve/main/special_tokens_map.json
- Command line
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hf download hf://Raffay/local_speech_processing_project_wav2vec2/special_tokens_map.json
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curl -L -o special_tokens_map.json https://huggingface.co/Raffay/local_speech_processing_project_wav2vec2/resolve/main/special_tokens_map.json
85 Bytes
| {"bos_token": "<s>", "eos_token": "</s>", "unk_token": "[UNK]", "pad_token": "[PAD]"} |