Instructions to use lnxdx/19_2000_1e-5_hp-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lnxdx/19_2000_1e-5_hp-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="lnxdx/19_2000_1e-5_hp-base")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("lnxdx/19_2000_1e-5_hp-base") model = AutoModelForCTC.from_pretrained("lnxdx/19_2000_1e-5_hp-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from lnxdx/19_2000_1e-5_hp-base: direct link, hf CLI and curl.
- Browser
- Download file 4.66 kB
-
https://huggingface.co/lnxdx/19_2000_1e-5_hp-base/resolve/main/training_args.bin
- Command line
-
hf download hf://lnxdx/19_2000_1e-5_hp-base/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/lnxdx/19_2000_1e-5_hp-base/resolve/main/training_args.bin
4.66 kB
- Xet hash:
- d157dfb123cd16a35e7270d351371e04962f490605ff318967b2d4f50e3a9792
- Size of remote file:
- 4.66 kB
- SHA256:
- a3a6e76ce66457592fc27ec5dca1633c2db4d07fda9f003b4d738557d0a30d6d
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