Instructions to use arpanl/models-moved with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use arpanl/models-moved with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="arpanl/models-moved") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("arpanl/models-moved") model = AutoModelForImageClassification.from_pretrained("arpanl/models-moved", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 320
Browse files
runs/Apr29_09-19-27_a360-serv1/events.out.tfevents.1714396772.a360-serv1.1425351.0
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:89d09a68bc87cd176f63b2293f7132c3dba384a9625951534d8a1d09667ea68c
|
| 3 |
+
size 10968
|