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 trainer_state.json from razhan/whisper-base-hac: direct link, hf CLI and curl.
- Browser
- Download file 4.61 kB
-
https://huggingface.co/razhan/whisper-base-hac/resolve/main/trainer_state.json
- Command line
-
hf download hf://razhan/whisper-base-hac/trainer_state.json
-
curl -L -o trainer_state.json https://huggingface.co/razhan/whisper-base-hac/resolve/main/trainer_state.json
4.61 kB
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