Instructions to use darinchau/checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use darinchau/checkpoints with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="darinchau/checkpoints")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("darinchau/checkpoints") model = AutoModelForSpeechSeq2Seq.from_pretrained("darinchau/checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 1800
Browse files- model.safetensors +1 -1
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 290403936
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b6379982fd07ef50f74c10f7f167ec2b42fcf26a2fc596ec0055c94cad2282eb
|
| 3 |
size 290403936
|