Instructions to use Benjaminpwh/sst-en_de_13 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Benjaminpwh/sst-en_de_13 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, DynamicWav2Vec2ForCTC processor = AutoProcessor.from_pretrained("Benjaminpwh/sst-en_de_13") model = DynamicWav2Vec2ForCTC.from_pretrained("Benjaminpwh/sst-en_de_13", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Benjaminpwh/sst-en_de_13: direct link, hf CLI and curl.
- Browser
- Download file 11.4 MB
-
https://huggingface.co/Benjaminpwh/sst-en_de_13/resolve/main/tokenizer.json
- Command line
-
hf download hf://Benjaminpwh/sst-en_de_13/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Benjaminpwh/sst-en_de_13/resolve/main/tokenizer.json
11.4 MB
- Xet hash:
- 693ec4b3922b0bd306bf7b4989e115ffbfeb7b0c08b31bc6d956818c6bb07f61
- Size of remote file:
- 11.4 MB
- SHA256:
- aeb13307a71acd8fe81861d94ad54ab689df773318809eed3cbe794b4492dae4
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