Instructions to use Sebastianpinar/lora2-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sebastianpinar/lora2-3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Sebastianpinar/lora2-3") 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/lora2-3") model = AutoModelForImageClassification.from_pretrained("Sebastianpinar/lora2-3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model
Verified signatureThis is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.49cc5d3
-
Training in progress, epoch 36
c0b65dd -
Training in progress, epoch 32
169a655 -
Training in progress, epoch 25
fe4b332 -
Training in progress, epoch 20
cc28d0d -
Training in progress, epoch 16
7b12a17 -
Training in progress, epoch 10
faa472b -
Training in progress, epoch 5
945b6e7 -
Training in progress, epoch 0
bbc9581 -
initial commit
7e6bb03