Instructions to use Evan-Lin/trainer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Evan-Lin/trainer with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="Evan-Lin/trainer")# Load model directly from transformers import AutoFeatureExtractor, AutoModelForAudioClassification extractor = AutoFeatureExtractor.from_pretrained("Evan-Lin/trainer") model = AutoModelForAudioClassification.from_pretrained("Evan-Lin/trainer", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 238925af405d27a28cd408c24cfc0a065d0513b6d699989adb45a3995323d9cd
- Size of remote file:
- 3.58 kB
- SHA256:
- 8268e27505c0f2c605823981254122a2174a708d9778fc3fdaa1c9cb6e45eadc
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.