Instructions to use hadiqa123/XLS-R_timit_en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hadiqa123/XLS-R_timit_en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hadiqa123/XLS-R_timit_en")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("hadiqa123/XLS-R_timit_en") model = AutoModelForCTC.from_pretrained("hadiqa123/XLS-R_timit_en", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from hadiqa123/XLS-R_timit_en: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/hadiqa123/XLS-R_timit_en/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://hadiqa123/XLS-R_timit_en@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/hadiqa123/XLS-R_timit_en/resolve/refs%2Fpr%2F1/pytorch_model.bin
1.26 GB
- Xet hash:
- 2e557e2a4386c34e96dd58d7d560c5459885eb1ccfbcef5ab91948bedcb66c35
- Size of remote file:
- 1.26 GB
- SHA256:
- c7ed065b494b9c28c3a2441e164f76c87eb2416fd43f24eee549397d3806419d
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