Instructions to use hf-internal-testing/tiny-random-Speech2TextModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-Speech2TextModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hf-internal-testing/tiny-random-Speech2TextModel")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("hf-internal-testing/tiny-random-Speech2TextModel") model = AutoModelForMultimodalLM.from_pretrained("hf-internal-testing/tiny-random-Speech2TextModel") - Notebooks
- Google Colab
- Kaggle
File size: 301 Bytes
7c6e63b | 1 2 3 4 5 6 7 8 9 10 11 12 13 | {
"do_ceptral_normalize": true,
"feature_extractor_type": "Speech2TextFeatureExtractor",
"feature_size": 24,
"normalize_means": true,
"normalize_vars": true,
"num_mel_bins": 24,
"padding_side": "right",
"padding_value": 0.0,
"return_attention_mask": true,
"sampling_rate": 16000
}
|