Audio Classification
Transformers
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Eval Results (legacy)
Instructions to use ashdev01/my_awesome_mind_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ashdev01/my_awesome_mind_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="ashdev01/my_awesome_mind_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("ashdev01/my_awesome_mind_model") model = AutoModelForAudioClassification.from_pretrained("ashdev01/my_awesome_mind_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ashdev01/my_awesome_mind_model: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/ashdev01/my_awesome_mind_model/resolve/main/training_args.bin
- Command line
-
hf download hf://ashdev01/my_awesome_mind_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ashdev01/my_awesome_mind_model/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 005ec3bb0e496643bb64578a95517109359690fd1bb49d9c1794e612de77d018
- Size of remote file:
- 5.11 kB
- SHA256:
- 5829e32f979b64e4ea4891990deca8c10673d3eb17ec915698455323774f351f
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