Instructions to use mohitsha/whisper-tiny-smooth-quant with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mohitsha/whisper-tiny-smooth-quant with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mohitsha/whisper-tiny-smooth-quant")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("mohitsha/whisper-tiny-smooth-quant") model = AutoModelForSpeechSeq2Seq.from_pretrained("mohitsha/whisper-tiny-smooth-quant") - Notebooks
- Google Colab
- Kaggle
Upload encoder_model_quantized.onnx with huggingface_hub
Browse files
encoder_model_quantized.onnx
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d473e48c78a2054fa7818c6388e8c0d64e5de5108e78d32779fd09faa0f8f4fc
|
| 3 |
+
size 11812287
|