Instructions to use Sebastianpinar/lora2-31 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sebastianpinar/lora2-31 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Sebastianpinar/lora2-31") 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("Sebastianpinar/lora2-31") model = AutoModelForImageClassification.from_pretrained("Sebastianpinar/lora2-31", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
83ecbe9
1
Parent(s): e8adaa6
Training in progress, epoch 1
Browse files- pytorch_model.bin +1 -1
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1222250677
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:97702c981ae67a19b845406ea3e409674dd3bd500ac63caf12bad2f6b90fd36d
|
| 3 |
size 1222250677
|