Instructions to use Sebastianpinar/lora2-70 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sebastianpinar/lora2-70 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Sebastianpinar/lora2-70") 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/lora2-70") model = AutoModelForImageClassification.from_pretrained("Sebastianpinar/lora2-70", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
a2db0de
1
Parent(s): 8144a48
Training in progress, epoch 19
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 1219995701
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:1e7c7b2435a89be9a4d1ed66f43a2c8a94aa3d49aa04be810500bab37afbf2e3
|
| 3 |
size 1219995701
|