Instructions to use Marialab/finetuned-s2t-1000-step with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Marialab/finetuned-s2t-1000-step with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Marialab/finetuned-s2t-1000-step")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Marialab/finetuned-s2t-1000-step") model = AutoModelForSpeechSeq2Seq.from_pretrained("Marialab/finetuned-s2t-1000-step", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Marialab/finetuned-s2t-1000-step: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/Marialab/finetuned-s2t-1000-step/resolve/main/training_args.bin
- Command line
-
hf download hf://Marialab/finetuned-s2t-1000-step/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Marialab/finetuned-s2t-1000-step/resolve/main/training_args.bin
5.5 kB
- Xet hash:
- 7bbfb9fee75b3264bbdaea3dbd8f024ce3ce33d1615a7e7834f27bbd0437d18a
- Size of remote file:
- 5.5 kB
- SHA256:
- 16e44452bbb9409a31659a9dabae34a04b6c5b3ba8d2f33a9371024df6450d78
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