Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Arabic
whisper
hf-asr-leaderboard
Generated from Trainer
Instructions to use smerchi/Arabic-Morocco-Speech_To_Text with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use smerchi/Arabic-Morocco-Speech_To_Text with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="smerchi/Arabic-Morocco-Speech_To_Text")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("smerchi/Arabic-Morocco-Speech_To_Text") model = AutoModelForSpeechSeq2Seq.from_pretrained("smerchi/Arabic-Morocco-Speech_To_Text", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb403a65a9189b1509516a36052c459e76ead988ce5ab35f43913c1e5a30185e
- Size of remote file:
- 4.35 kB
- SHA256:
- c7d61c63e9917db65b067e3814d4f238e68fc7db02930fe3e45cead7d13bc8a4
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