Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
wav2vec2-bert
Generated from Trainer
Eval Results (legacy)
Instructions to use web2savar/w2v-fine-tune-test-no-punct2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use web2savar/w2v-fine-tune-test-no-punct2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="web2savar/w2v-fine-tune-test-no-punct2")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("web2savar/w2v-fine-tune-test-no-punct2") model = AutoModelForCTC.from_pretrained("web2savar/w2v-fine-tune-test-no-punct2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from web2savar/w2v-fine-tune-test-no-punct2: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/web2savar/w2v-fine-tune-test-no-punct2/resolve/main/training_args.bin
- Command line
-
hf download hf://web2savar/w2v-fine-tune-test-no-punct2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/web2savar/w2v-fine-tune-test-no-punct2/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- ab2720ecf2422ecc401d662ef5036da0e1f9506a438eb44224dcd7c3b22720af
- Size of remote file:
- 4.73 kB
- SHA256:
- d407f4aeff0f2f88f5204e74330011ba2cc7313722cc3930328741519e6168f6
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