Instructions to use pnparam/switch_hyp22 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pnparam/switch_hyp22 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="pnparam/switch_hyp22")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("pnparam/switch_hyp22") model = AutoModelForCTC.from_pretrained("pnparam/switch_hyp22") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:5a3f5cd33a811bc0bca6e1c9901b1a93b6ee8f36a48fbb1af4b73211fe27d346
|
| 3 |
+
size 1261905824
|