Instructions to use Sebastianpinar/lora-9 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sebastianpinar/lora-9 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Sebastianpinar/lora-9") 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/lora-9") model = AutoModelForImageClassification.from_pretrained("Sebastianpinar/lora-9", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
1823fde
1
Parent(s): ea9f69a
Training in progress, epoch 20
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 345763125
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0082dea6fef20d0e391298da8098ce066f55e6182307e6806ddb55f9633e8325
|
| 3 |
size 345763125
|