Automatic Speech Recognition
Transformers
Safetensors
Finnish
wav2vec2
finnish
Eval Results (legacy)
Instructions to use GetmanY1/wav2vec2-base-fi-lp-cont-pt-100h with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GetmanY1/wav2vec2-base-fi-lp-cont-pt-100h with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="GetmanY1/wav2vec2-base-fi-lp-cont-pt-100h")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("GetmanY1/wav2vec2-base-fi-lp-cont-pt-100h") model = AutoModelForCTC.from_pretrained("GetmanY1/wav2vec2-base-fi-lp-cont-pt-100h", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a00d0ff66f4e2edd2aaf91d01ae47d26fc52d578b7ac6d40ef4beefe2ee95bb2
- Size of remote file:
- 378 MB
- SHA256:
- 00c0b1db2b907bf16011b95bb1634bb405e912516375a127a8259d681a8d4ef8
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