Automatic Speech Recognition
Transformers
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use razhan/whisper-base-mzn with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use razhan/whisper-base-mzn with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="razhan/whisper-base-mzn")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("razhan/whisper-base-mzn") model = AutoModelForSpeechSeq2Seq.from_pretrained("razhan/whisper-base-mzn", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from razhan/whisper-base-mzn: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/razhan/whisper-base-mzn/resolve/main/training_args.bin
- Command line
-
hf download hf://razhan/whisper-base-mzn/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/razhan/whisper-base-mzn/resolve/main/training_args.bin
5.5 kB
- Xet hash:
- b2a2670438a72277abc9f1728db243a7913c0e8a875e86624625d511ea9bc78b
- Size of remote file:
- 5.5 kB
- SHA256:
- 58a5dfe247086afe54ad76f8c793995f1bef99fcb461a76a54fb4db5c1f16acb
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