Instructions to use anderloh/HuggingfaceBestModel2ClassEasy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anderloh/HuggingfaceBestModel2ClassEasy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="anderloh/HuggingfaceBestModel2ClassEasy")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("anderloh/HuggingfaceBestModel2ClassEasy") model = AutoModelForAudioClassification.from_pretrained("anderloh/HuggingfaceBestModel2ClassEasy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from anderloh/HuggingfaceBestModel2ClassEasy: direct link, hf CLI and curl.
- Browser
- Download file 52.1 MB
-
https://huggingface.co/anderloh/HuggingfaceBestModel2ClassEasy/resolve/main/model.safetensors
- Command line
-
hf download hf://anderloh/HuggingfaceBestModel2ClassEasy/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/anderloh/HuggingfaceBestModel2ClassEasy/resolve/main/model.safetensors
52.1 MB
- Xet hash:
- 4d4e4542fead3ea90f04f27d3b97843079c231b9ba47ade8a213aaca1aba2346
- Size of remote file:
- 52.1 MB
- SHA256:
- 3099375b7d1fde7be7f4a0a0f66f570bca8fc5e9b16260b822168d829977b229
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