Instructions to use aggtamv/Wav2vec2Askisi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aggtamv/Wav2vec2Askisi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="aggtamv/Wav2vec2Askisi")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("aggtamv/Wav2vec2Askisi") model = AutoModelForCTC.from_pretrained("aggtamv/Wav2vec2Askisi") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- .gitattributes +1 -0
- model.safetensors +3 -0
.gitattributes
ADDED
|
@@ -0,0 +1 @@
|
|
|
|
|
|
|
| 1 |
+
model.safetensors filter=lfs diff=lfs merge=lfs -text
|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:ea94a9507521057fc7abf6f357d033fa9fee6d44f1c84c80bd4d5104de693214
|
| 3 |
+
size 1261926332
|