Automatic Speech Recognition
Transformers
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use mouseyy/result_data_2-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mouseyy/result_data_2-4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mouseyy/result_data_2-4")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("mouseyy/result_data_2-4") model = AutoModelForCTC.from_pretrained("mouseyy/result_data_2-4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 31f0ff2923c71e907d8609ddcb9d3b58fde7af9e459c9b80040687072b082c60
- Size of remote file:
- 5.43 kB
- SHA256:
- 853893324eb07344fdec49bd69f27d31740bbdb6f6022ac3513a1741e7fe8b2a
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