Automatic Speech Recognition
Transformers
PyTorch
Hebrew
whisper
Generated from Trainer
Eval Results (legacy)
Instructions to use Alex2575/aleksis_heb_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Alex2575/aleksis_heb_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Alex2575/aleksis_heb_base")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Alex2575/aleksis_heb_base") model = AutoModelForSpeechSeq2Seq.from_pretrained("Alex2575/aleksis_heb_base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Alex2575/aleksis_heb_base: direct link, hf CLI and curl.
- Browser
- Download file 4.22 kB
-
https://huggingface.co/Alex2575/aleksis_heb_base/resolve/main/training_args.bin
- Command line
-
hf download hf://Alex2575/aleksis_heb_base/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Alex2575/aleksis_heb_base/resolve/main/training_args.bin
4.22 kB
- Xet hash:
- 004865acbc0f4d8f9d0dc9afeebaf5089bc3e57b644a123cea0433a0b09a0668
- Size of remote file:
- 4.22 kB
- SHA256:
- a88e937cfa56d95aae1f4e01a60a1deacb4cd001e045607c563ed4ff7ebbceef
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