Instructions to use Sebastianpinar/lora2-43 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sebastianpinar/lora2-43 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Sebastianpinar/lora2-43") 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/lora2-43") model = AutoModelForImageClassification.from_pretrained("Sebastianpinar/lora2-43", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
f028de5
1
Parent(s): 3af7f61
Training in progress, epoch 2
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 1220504117
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:ce9d84c5a2dd27136893f86408994a46bec8b9149171ce0fc39faf907bce2441
|
| 3 |
size 1220504117
|