Instructions to use Sebastianpinar/lora2-45 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sebastianpinar/lora2-45 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Sebastianpinar/lora2-45") 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/lora2-45") model = AutoModelForImageClassification.from_pretrained("Sebastianpinar/lora2-45", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
3fdda5d
1
Parent(s): 12118f2
Training in progress, epoch 4
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 1219872693
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:6b451edb3e9eec6a62f21cfa44317f84044c7807a3a29486a5e1098a904116de
|
| 3 |
size 1219872693
|