Instructions to use perisolb/dialektmodel-unique_speakers03 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use perisolb/dialektmodel-unique_speakers03 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="perisolb/dialektmodel-unique_speakers03")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("perisolb/dialektmodel-unique_speakers03") model = AutoModelForAudioClassification.from_pretrained("perisolb/dialektmodel-unique_speakers03", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from perisolb/dialektmodel-unique_speakers03: direct link, hf CLI and curl.
- Browser
- Download file 3.06 kB
-
https://huggingface.co/perisolb/dialektmodel-unique_speakers03/resolve/main/training_args.bin
- Command line
-
hf download hf://perisolb/dialektmodel-unique_speakers03/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/perisolb/dialektmodel-unique_speakers03/resolve/main/training_args.bin
3.06 kB
- Xet hash:
- b06ef95c148d1d0e56f65f5e10f269ecd68153327e64878977e84370ffe4cb45
- Size of remote file:
- 3.06 kB
- SHA256:
- 29265b0a6fe47836448b40c39acf4b40c976e83360d67c7a1aad190c1ec6d9e2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.