Automatic Speech Recognition
Transformers
Safetensors
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use razhan/whisper-base-hac with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use razhan/whisper-base-hac with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="razhan/whisper-base-hac")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("razhan/whisper-base-hac") model = AutoModelForSpeechSeq2Seq.from_pretrained("razhan/whisper-base-hac", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from razhan/whisper-base-hac: direct link, hf CLI and curl.
- Browser
- Download file 5.5 kB
-
https://huggingface.co/razhan/whisper-base-hac/resolve/main/training_args.bin
- Command line
-
hf download hf://razhan/whisper-base-hac/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/razhan/whisper-base-hac/resolve/main/training_args.bin
5.5 kB
- Xet hash:
- 36582b07aaecfc3a75974ad66bee9e5bd1d0fb41e5671e15327a41edc5ee6436
- Size of remote file:
- 5.5 kB
- SHA256:
- 522d79f6a4ea424747f934bf89f34656b458ec8945345ca9575860ae1a0ebec7
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