Instructions to use shrria/bts-asr-processor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shrria/bts-asr-processor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="shrria/bts-asr-processor")# Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("shrria/bts-asr-processor") model = AutoModelForCTC.from_pretrained("shrria/bts-asr-processor") - 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:f0135130a25f0f16a59cc376f886f9e54e0c1736f1b85c4c01e93b9f4cc4b090
|
| 3 |
+
size 1262102632
|