Instructions to use Eimhin03/outout_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Eimhin03/outout_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Eimhin03/outout_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Eimhin03/outout_model") model = AutoModelForSpeechSeq2Seq.from_pretrained("Eimhin03/outout_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Eimhin03/outout_model: direct link, hf CLI and curl.
- Browser
- Download file 5.33 kB
-
https://huggingface.co/Eimhin03/outout_model/resolve/main/training_args.bin
- Command line
-
hf download hf://Eimhin03/outout_model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Eimhin03/outout_model/resolve/main/training_args.bin
5.33 kB
- Xet hash:
- ea1be9defcb34d35328344c3a185a1ada822575e2446e4775324c75dcd92604d
- Size of remote file:
- 5.33 kB
- SHA256:
- 5cc69e86308bca9eb1827c3f421074db36def0e35d7968494e1385d8332635a4
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