Instructions to use yarik921/Teflon_0.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yarik921/Teflon_0.2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="yarik921/Teflon_0.2")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("yarik921/Teflon_0.2") model = AutoModelForCTC.from_pretrained("yarik921/Teflon_0.2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from yarik921/Teflon_0.2: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/yarik921/Teflon_0.2/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://yarik921/Teflon_0.2/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/yarik921/Teflon_0.2/resolve/main/pytorch_model.bin
1.26 GB
- Xet hash:
- f840387c8a12c67e8e21b396ef1fae82535bf0918573c53d441b46a9b3fc8ee1
- Size of remote file:
- 1.26 GB
- SHA256:
- 910faa89215ceec2f0d59067ecec621e3d83e3c17732bddc99f1d45214617f48
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