Instructions to use Abdallah151/DabljaAR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Abdallah151/DabljaAR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Abdallah151/DabljaAR")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("Abdallah151/DabljaAR") model = AutoModelForMultimodalLM.from_pretrained("Abdallah151/DabljaAR", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from Abdallah151/DabljaAR: direct link, hf CLI and curl.
- Browser
- Download file 357 Bytes
-
https://huggingface.co/Abdallah151/DabljaAR/resolve/main/preprocessor_config.json
- Command line
-
hf download hf://Abdallah151/DabljaAR/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/Abdallah151/DabljaAR/resolve/main/preprocessor_config.json
357 Bytes
| { | |
| "chunk_length": 30, | |
| "dither": 0.0, | |
| "feature_extractor_type": "WhisperFeatureExtractor", | |
| "feature_size": 128, | |
| "hop_length": 160, | |
| "n_fft": 400, | |
| "n_samples": 480000, | |
| "nb_max_frames": 3000, | |
| "padding_side": "right", | |
| "padding_value": 0.0, | |
| "processor_class": "Qwen3ASRProcessor", | |
| "return_attention_mask": true, | |
| "sampling_rate": 16000 | |
| } | |