Automatic Speech Recognition
Transformers
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use mouseyy/result_data_2-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mouseyy/result_data_2-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mouseyy/result_data_2-1")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("mouseyy/result_data_2-1") model = AutoModelForCTC.from_pretrained("mouseyy/result_data_2-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3d13d431bad25017e0be4653a9b4758314ac06ec3dfdb43940f1de24715fe7d8
- Size of remote file:
- 5.43 kB
- SHA256:
- b5f68598c10ab6c5b6de95e2c17aa4fd0a9b5dd2bc9d41daa0be1042841df94b
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