Automatic Speech Recognition
Transformers
PyTorch
Safetensors
Turkish
wav2vec2
audio
speech
xlsr-fine-tuning-week
Eval Results (legacy)
Instructions to use ceyda/wav2vec2-base-760-turkish with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ceyda/wav2vec2-base-760-turkish with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ceyda/wav2vec2-base-760-turkish")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("ceyda/wav2vec2-base-760-turkish") model = AutoModelForCTC.from_pretrained("ceyda/wav2vec2-base-760-turkish", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ceyda/wav2vec2-base-760-turkish: direct link, hf CLI and curl.
- Browser
- Download file 378 MB
-
https://huggingface.co/ceyda/wav2vec2-base-760-turkish/resolve/76ee6a1abeee9f23f2968f997c2fad05be2d4b84/pytorch_model.bin
- Command line
-
hf download hf://ceyda/wav2vec2-base-760-turkish@76ee6a1abeee9f23f2968f997c2fad05be2d4b84/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ceyda/wav2vec2-base-760-turkish/resolve/76ee6a1abeee9f23f2968f997c2fad05be2d4b84/pytorch_model.bin
378 MB
- Xet hash:
- 4f3b45f7f5aac70e038c6bf73df03844bfc5021cf45c6f8e5ad2925ec74f31c8
- Size of remote file:
- 378 MB
- SHA256:
- adeefd83b89a25212c0d6c74b43b28e367e54cc7fbce63599927f7bc6d2b8ae9
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