Instructions to use hf-tiny-model-private/tiny-random-UniSpeechForCTC with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-tiny-model-private/tiny-random-UniSpeechForCTC with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="hf-tiny-model-private/tiny-random-UniSpeechForCTC")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("hf-tiny-model-private/tiny-random-UniSpeechForCTC") model = AutoModelForCTC.from_pretrained("hf-tiny-model-private/tiny-random-UniSpeechForCTC") - 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 sha256:8cefb105b325c29494a748ebcfe38ed3d24bf6f72b245756bd1988ca8feb7565
|
| 3 |
+
size 118176
|