Instructions to use rfhuang/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rfhuang/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="rfhuang/results")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("rfhuang/results") model = AutoModelForAudioClassification.from_pretrained("rfhuang/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from rfhuang/results: direct link, hf CLI and curl.
- Browser
- Download file 5.05 kB
-
https://huggingface.co/rfhuang/results/resolve/main/training_args.bin
- Command line
-
hf download hf://rfhuang/results/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/rfhuang/results/resolve/main/training_args.bin
5.05 kB
- Xet hash:
- c027690ee789e7b46e9318ee28f3f916c353d25c856cbe27db0e8492f31b9ce3
- Size of remote file:
- 5.05 kB
- SHA256:
- f8ebb5c074c4e876e9fc8efe315a3c92065e285f90c78f90ff52120898cba067
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