Instructions to use danielgi97/whisper-medium-lara-Raquel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use danielgi97/whisper-medium-lara-Raquel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="danielgi97/whisper-medium-lara-Raquel")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("danielgi97/whisper-medium-lara-Raquel") model = AutoModelForSpeechSeq2Seq.from_pretrained("danielgi97/whisper-medium-lara-Raquel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from danielgi97/whisper-medium-lara-Raquel: direct link, hf CLI and curl.
- Browser
- Download file 5.18 kB
-
https://huggingface.co/danielgi97/whisper-medium-lara-Raquel/resolve/main/training_args.bin
- Command line
-
hf download hf://danielgi97/whisper-medium-lara-Raquel/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/danielgi97/whisper-medium-lara-Raquel/resolve/main/training_args.bin
5.18 kB
- Xet hash:
- dba1643eecd38626613ebb396f3979ac8a4687384ccb6892f97a2639d6d7abed
- Size of remote file:
- 5.18 kB
- SHA256:
- ac65ca38fa889a2cf7ee6b47f7be140d2ebb63b3b694b91ff56b6342d2bff073
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