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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Initial upload: Gemma 4 audio encoder (304.8M USM-style Conformer)
Browse files- model.safetensors +2 -2
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:e3d409ff33a1e3bdbe4b2b721971e4985a349d6599ecefa725ea819c00306bb4
|
| 3 |
+
size 609732672
|