Instructions to use lsb/tironiculum with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lsb/tironiculum with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="lsb/tironiculum")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("lsb/tironiculum") model = AutoModelForCTC.from_pretrained("lsb/tironiculum") - Notebooks
- Google Colab
- Kaggle
add tokenizer
Browse files
runs/May09_07-45-36_161e07b90923/1652082838.6917603/events.out.tfevents.1652082838.161e07b90923.96.1
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:687f4c3ae90fcc62ad1327decb757703ebdbefb93de6c54d0324b9d7e781c1bc
|
| 3 |
+
size 4887
|
runs/May09_07-45-36_161e07b90923/events.out.tfevents.1652082838.161e07b90923.96.0
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:35a326ef2899ca1275dd71d00b224358014e24a1d6e7f33bb3e8329e11819016
|
| 3 |
+
size 48538
|