Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use fequed/my_awesome_mind_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fequed/my_awesome_mind_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="fequed/my_awesome_mind_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("fequed/my_awesome_mind_model") model = AutoModelForAudioClassification.from_pretrained("fequed/my_awesome_mind_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from fequed/my_awesome_mind_model: direct link, hf CLI and curl.
- Browser
- Download file 4.92 kB
-
https://huggingface.co/fequed/my_awesome_mind_model/resolve/main/training_args.bin
- Command line
-
hf download hf://fequed/my_awesome_mind_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/fequed/my_awesome_mind_model/resolve/main/training_args.bin
4.92 kB
- Xet hash:
- 5524b89e973ae54257b9d3c83a6ae652cf2712e45c984729272e876fdfef31d3
- Size of remote file:
- 4.92 kB
- SHA256:
- 0d62fc4ba81421b17a9292adfa9fc87568e0ddddfcd6b306dc6b45a0698d413e
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