Instructions to use Sebastianpinar/lora2-10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sebastianpinar/lora2-10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Sebastianpinar/lora2-10") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Sebastianpinar/lora2-10") model = AutoModelForImageClassification.from_pretrained("Sebastianpinar/lora2-10") - Notebooks
- Google Colab
- Kaggle
Commit ·
8f6d790
1
Parent(s): 4398c51
Training in progress, epoch 37
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 1219831733
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b847ebd91c0f5c05bfad936415ebf8e385b9d9af13fbc5b46921d132743d05f5
|
| 3 |
size 1219831733
|