Instructions to use mohitsha/whisper-tiny-static-shape-quantized-SL-448 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mohitsha/whisper-tiny-static-shape-quantized-SL-448 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="mohitsha/whisper-tiny-static-shape-quantized-SL-448")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("mohitsha/whisper-tiny-static-shape-quantized-SL-448") model = AutoModelForSpeechSeq2Seq.from_pretrained("mohitsha/whisper-tiny-static-shape-quantized-SL-448") - Notebooks
- Google Colab
- Kaggle
Upload decoder_model_quantized_static_scatter.onnx
Browse files
decoder_model_quantized_static_scatter.onnx
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:beb38ca649c013239e673b86fa9630bd508bbb22ea30af9929b05cd4007bcff0
|
| 3 |
+
size 94025161
|