Automatic Speech Recognition
Transformers
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use mouseyy/result_data_2-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mouseyy/result_data_2-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mouseyy/result_data_2-2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("mouseyy/result_data_2-2") model = AutoModelForCTC.from_pretrained("mouseyy/result_data_2-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 97015f0d7670fd5b98e15a2bbe5f853b0bcc6eaa87737f5b08b56de5c33cebe0
- Size of remote file:
- 5.43 kB
- SHA256:
- abd997ec374a3f504b2d3d027c7c1cad8d62e1a297e9aef92a9b4e17b4885901
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