Instructions to use Bronsn/whisper-tiny-luganda-final with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Bronsn/whisper-tiny-luganda-final with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="Bronsn/whisper-tiny-luganda-final")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("Bronsn/whisper-tiny-luganda-final") model = AutoModelForSpeechSeq2Seq.from_pretrained("Bronsn/whisper-tiny-luganda-final") - Notebooks
- Google Colab
- Kaggle
Upload checkpoints/checkpoint-2500/optimizer.pt with huggingface_hub
Browse files
checkpoints/checkpoint-2500/optimizer.pt
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:cf0ab91d5768f78d3763a4b81190a6084310126c7c2db75c71122231aa1dc606
|
| 3 |
+
size 297619258
|