Instructions to use hf-internal-testing/tiny-random-MoonshineForConditionalGeneration with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-MoonshineForConditionalGeneration with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hf-internal-testing/tiny-random-MoonshineForConditionalGeneration")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-MoonshineForConditionalGeneration") model = AutoModelForSpeechSeq2Seq.from_pretrained("hf-internal-testing/tiny-random-MoonshineForConditionalGeneration") - Notebooks
- Google Colab
- Kaggle
File size: 257 Bytes
9acdc31 | 1 2 3 4 5 6 7 8 9 10 11 | {
"do_normalize": false,
"feature_extractor_type": "Wav2Vec2FeatureExtractor",
"feature_size": 1,
"padding_side": "right",
"padding_value": 0.0,
"processor_class": "Wav2Vec2Processor",
"return_attention_mask": true,
"sampling_rate": 16000
}
|