Automatic Speech Recognition
Transformers
Safetensors
Mobilint
mobilint-whisper
text-generation
custom_code
Instructions to use mobilint/whisper-medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mobilint/whisper-medium with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mobilint/whisper-medium", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("mobilint/whisper-medium", trust_remote_code=True, device_map="auto") - Mobilint
How to use mobilint/whisper-medium with Mobilint:
# pip install mblt-model-zoo from mblt_model_zoo.vision import MBLT_Engine model = MBLT_Engine( model_cls="whisper-medium", model_type="DEFAULT", model_path="", core_mode="global8", ) try: image = model.preprocess("path/to/image.jpg") output = model(image) result = model.postprocess(output) finally: model.dispose() - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from mobilint/whisper-medium: direct link, hf CLI and curl.
- Browser
- Download file 2.48 MB
-
https://huggingface.co/mobilint/whisper-medium/resolve/main/tokenizer.json
- Command line
-
hf download hf://mobilint/whisper-medium/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/mobilint/whisper-medium/resolve/main/tokenizer.json
2.48 MB
File too large to display, you can check the raw version instead.