Instructions to use trl-internal-testing/tiny-Qwen2AudioForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use trl-internal-testing/tiny-Qwen2AudioForConditionalGeneration with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("trl-internal-testing/tiny-Qwen2AudioForConditionalGeneration") model = AutoModelForMultimodalLM.from_pretrained("trl-internal-testing/tiny-Qwen2AudioForConditionalGeneration", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download preprocessor_config.json from trl-internal-testing/tiny-Qwen2AudioForConditionalGeneration: direct link, hf CLI and curl.
- Browser
- Download file 359 Bytes
-
https://huggingface.co/trl-internal-testing/tiny-Qwen2AudioForConditionalGeneration/resolve/7bff21b2d3ceb00ee2addca1d99166121e62e093/preprocessor_config.json
- Command line
-
hf download hf://trl-internal-testing/tiny-Qwen2AudioForConditionalGeneration@7bff21b2d3ceb00ee2addca1d99166121e62e093/preprocessor_config.json
-
curl -L -o preprocessor_config.json https://huggingface.co/trl-internal-testing/tiny-Qwen2AudioForConditionalGeneration/resolve/7bff21b2d3ceb00ee2addca1d99166121e62e093/preprocessor_config.json
359 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": "Qwen2AudioProcessor", | |
| "return_attention_mask": true, | |
| "sampling_rate": 16000 | |
| } | |