Instructions to use hshispeech/Ruby-ASR-1.7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hshispeech/Ruby-ASR-1.7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hshispeech/Ruby-ASR-1.7B")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hshispeech/Ruby-ASR-1.7B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download subtitle/preprocessor_config.json from hshispeech/Ruby-ASR-1.7B: direct link, hf CLI and curl.
- Browser
- Download file 330 Bytes
-
https://huggingface.co/hshispeech/Ruby-ASR-1.7B/resolve/main/subtitle/preprocessor_config.json
- Command line
-
hf download hf://hshispeech/Ruby-ASR-1.7B/subtitle/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/hshispeech/Ruby-ASR-1.7B/resolve/main/subtitle/preprocessor_config.json
330 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 | |
| } |