Instructions to use dmusingu/luganda_wav2vec2_ctc_reg with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dmusingu/luganda_wav2vec2_ctc_reg with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="dmusingu/luganda_wav2vec2_ctc_reg")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("dmusingu/luganda_wav2vec2_ctc_reg") model = AutoModelForCTC.from_pretrained("dmusingu/luganda_wav2vec2_ctc_reg", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 1000
Browse files- model.safetensors +1 -1
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1261950980
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c27b680dc32a0aa7eebf9eb9fc43b837a26b849788244427c6a971e314a1c603
|
| 3 |
size 1261950980
|