Instructions to use rkmt/wav2vec2-base-timit-demo-colab with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rkmt/wav2vec2-base-timit-demo-colab with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="rkmt/wav2vec2-base-timit-demo-colab")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("rkmt/wav2vec2-base-timit-demo-colab") model = AutoModelForCTC.from_pretrained("rkmt/wav2vec2-base-timit-demo-colab", device_map="auto") - Notebooks
- Google Colab
- Kaggle
End of training
Browse files
runs/Dec29_12-57-55_rkmtk2/events.out.tfevents.1640750517.rkmtk2.194273.2
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 sha256:52b81d02cc232173069a3cec79707a1d21544e3a186a3e8171adc1691faacfa8
|
| 3 |
+
size 19585
|