Instructions to use niclas/ATC_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use niclas/ATC_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="niclas/ATC_1")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("niclas/ATC_1") model = AutoModelForCTC.from_pretrained("niclas/ATC_1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from niclas/ATC_1: direct link, hf CLI and curl.
- Browser
- Download file 2.86 kB
-
https://huggingface.co/niclas/ATC_1/resolve/main/training_args.bin
- Command line
-
hf download hf://niclas/ATC_1/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/niclas/ATC_1/resolve/main/training_args.bin
2.86 kB
- Xet hash:
- 87e94f7808dedbe664a1a4ed49fc6e14757a732e191ee77a8b5c3b3a29c10da7
- Size of remote file:
- 2.86 kB
- SHA256:
- 061267c38c214b70db647aa971be161a56bd0971234f976870f9c1905b517831
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