Automatic Speech Recognition
Transformers
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use mouseyy/result_data-4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mouseyy/result_data-4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mouseyy/result_data-4")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("mouseyy/result_data-4") model = AutoModelForCTC.from_pretrained("mouseyy/result_data-4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 2a50e890338a84e20620f7ba3321d84d502ddc8fc7970a5a9f63837e4e52676e
- Size of remote file:
- 5.37 kB
- SHA256:
- 7a63a445933c09fb868e76f90e79e243140985ea4f9449beb1c309e22e80065c
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