Feature Extraction
Transformers
Safetensors
English
multilingual
gemma4_audio
audio
speech
conformer
gemma4
usm
google
Eval Results (legacy)
Instructions to use rnagabh/gemma4-audio-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rnagabh/gemma4-audio-encoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="rnagabh/gemma4-audio-encoder")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("rnagabh/gemma4-audio-encoder") model = AutoModel.from_pretrained("rnagabh/gemma4-audio-encoder") - Notebooks
- Google Colab
- Kaggle
File size: 510 Bytes
8d87601 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | {
"feature_size": 128,
"sampling_rate": 16000,
"padding_value": 0.0,
"padding_side": "right",
"return_attention_mask": true,
"feature_extractor_type": "Gemma4AudioFeatureExtractor",
"fft_length": 512,
"frame_length": 320,
"hop_length": 160,
"min_frequency": 0.0,
"max_frequency": 8000.0,
"preemphasis": 0.0,
"preemphasis_htk_flavor": true,
"fft_overdrive": false,
"dither": 0.0,
"input_scale_factor": 1.0,
"mel_floor": 0.001,
"per_bin_mean": null,
"per_bin_stddev": null
} |