Instructions to use codingaslu/logs with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use codingaslu/logs with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="codingaslu/logs")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("codingaslu/logs") model = AutoModelForAudioClassification.from_pretrained("codingaslu/logs", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from codingaslu/logs: direct link, hf CLI and curl.
- Browser
- Download file 4.66 kB
-
https://huggingface.co/codingaslu/logs/resolve/main/training_args.bin
- Command line
-
hf download hf://codingaslu/logs/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/codingaslu/logs/resolve/main/training_args.bin
4.66 kB
- Xet hash:
- e77d7f5daa54b611a97421a4808a11efa1529967aa654f8d68643277a38989e7
- Size of remote file:
- 4.66 kB
- SHA256:
- fe373e8610b80c3e3e834b2f04b6818fc07289eb13caaa3dafc583337344e85e
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