Instructions to use wesam266/px with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wesam266/px with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="wesam266/px")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("wesam266/px") model = AutoModelForCTC.from_pretrained("wesam266/px", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from wesam266/px: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/wesam266/px/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://wesam266/px/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/wesam266/px/resolve/main/pytorch_model.bin
1.26 GB
- Xet hash:
- 717acd8f4cbae7dacf97e509d0ee4ccf204ab2e251a481849c8672a049541dd6
- Size of remote file:
- 1.26 GB
- SHA256:
- 2d8e0437f7579768f8d4dda260a5831b6803d5f4245a95c1587598ec045382f6
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