Instructions to use shtapm/output_large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shtapm/output_large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="shtapm/output_large")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("shtapm/output_large") model = AutoModelForSpeechSeq2Seq.from_pretrained("shtapm/output_large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from shtapm/output_large: direct link, hf CLI and curl.
- Browser
- Download file 5.11 kB
-
https://huggingface.co/shtapm/output_large/resolve/main/training_args.bin
- Command line
-
hf download hf://shtapm/output_large/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/shtapm/output_large/resolve/main/training_args.bin
5.11 kB
- Xet hash:
- 099cfe7557dec206c590a4adac2a485782eff71cf941331cc101060912911e85
- Size of remote file:
- 5.11 kB
- SHA256:
- 43e0685d21e0452dc1eca90eb238d5b011cc23e058b380f220a9c39e10506d76
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