Instructions to use EngSami/my_awesome_mind_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EngSami/my_awesome_mind_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="EngSami/my_awesome_mind_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("EngSami/my_awesome_mind_model") model = AutoModelForAudioClassification.from_pretrained("EngSami/my_awesome_mind_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from EngSami/my_awesome_mind_model: direct link, hf CLI and curl.
- Browser
- Download file 3.96 kB
-
https://huggingface.co/EngSami/my_awesome_mind_model/resolve/main/training_args.bin
- Command line
-
hf download hf://EngSami/my_awesome_mind_model/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/EngSami/my_awesome_mind_model/resolve/main/training_args.bin
3.96 kB
- Xet hash:
- dd7f772a0611fbf399c4695bd2522dad5fe21a3df092868ed261d31f56386003
- Size of remote file:
- 3.96 kB
- SHA256:
- 86805069bfbaea61b6b1b58ca47e80da8b7d0ea971f470f05f5297713e95977d
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