Audio Classification
Transformers
TensorBoard
Safetensors
data2vec-audio
Generated from Trainer
Eval Results (legacy)
Instructions to use Masataro/Testing_for_EEG with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Masataro/Testing_for_EEG with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Masataro/Testing_for_EEG")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForAudioClassification tokenizer = AutoTokenizer.from_pretrained("Masataro/Testing_for_EEG") model = AutoModelForAudioClassification.from_pretrained("Masataro/Testing_for_EEG", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Masataro/Testing_for_EEG: direct link, hf CLI and curl.
- Browser
- Download file 4.98 kB
-
https://huggingface.co/Masataro/Testing_for_EEG/resolve/main/training_args.bin
- Command line
-
hf download hf://Masataro/Testing_for_EEG/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Masataro/Testing_for_EEG/resolve/main/training_args.bin
4.98 kB
- Xet hash:
- 55b9bf81b30d04c4185b9c84a6187573e748e5ad2a0089c64ac1bf7fce857c6a
- Size of remote file:
- 4.98 kB
- SHA256:
- 172f5cc388d34cef34212aea374e5b73a52d5c1ca504d2b91a0a9a26274f2238
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