Instructions to use yarik921/Teflon_0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yarik921/Teflon_0.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="yarik921/Teflon_0.1")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("yarik921/Teflon_0.1") model = AutoModelForCTC.from_pretrained("yarik921/Teflon_0.1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from yarik921/Teflon_0.1: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/yarik921/Teflon_0.1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://yarik921/Teflon_0.1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/yarik921/Teflon_0.1/resolve/main/pytorch_model.bin
1.26 GB
- Xet hash:
- 0f75c03e70e34ea8b107421a1da66b95fdcd38ff5709e0fddc6522e353029159
- Size of remote file:
- 1.26 GB
- SHA256:
- e4fe58c03d5d805d3ca8ef9ef0c60df6e0cca7d6af5d851a735053e2057a40ef
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