Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
Safetensors
Italian
whisper
whisper-event
Generated from Trainer
Eval Results (legacy)
Instructions to use ALM/whisper-it-small-augmented with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ALM/whisper-it-small-augmented with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ALM/whisper-it-small-augmented")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("ALM/whisper-it-small-augmented") model = AutoModelForSpeechSeq2Seq.from_pretrained("ALM/whisper-it-small-augmented", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ALM/whisper-it-small-augmented: direct link, hf CLI and curl.
- Browser
- Download file 3.64 kB
-
https://huggingface.co/ALM/whisper-it-small-augmented/resolve/main/training_args.bin
- Command line
-
hf download hf://ALM/whisper-it-small-augmented/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ALM/whisper-it-small-augmented/resolve/main/training_args.bin
3.64 kB
- Xet hash:
- 10245fa37ca5721f8bcdfb0ff20234786c9c04fa86c1d644c47ab1f9bb0490fe
- Size of remote file:
- 3.64 kB
- SHA256:
- dedd057aa35eb6891b95427d585fe8637f023a04728881679486d3307a5c41d6
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