Image Classification
Transformers
ONNX
English
multi-head-classification
room-classification
dinov2
computer-vision
scene-classification
Instructions to use ondame/image-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ondame/image-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="ondame/image-classifier") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ondame/image-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -258,4 +258,4 @@ Apache 2.0 License
|
|
| 258 |
|
| 259 |
## ์ฐธ๊ณ
|
| 260 |
|
| 261 |
-
์ด ๋ชจ๋ธ์ Room Clusterer ํ๋ก์ ํธ์ ์ผ๋ถ๋ก ๊ฐ๋ฐ๋์์ต๋๋ค. ๋ ์์ธํ ์ ๋ณด๋ [ํ๋ก์ ํธ ์ ์ฅ์](https://github.com/
|
|
|
|
| 258 |
|
| 259 |
## ์ฐธ๊ณ
|
| 260 |
|
| 261 |
+
์ด ๋ชจ๋ธ์ Room Clusterer ํ๋ก์ ํธ์ ์ผ๋ถ๋ก ๊ฐ๋ฐ๋์์ต๋๋ค. ๋ ์์ธํ ์ ๋ณด๋ [ํ๋ก์ ํธ ์ ์ฅ์](https://github.com/tportio/content-ml-trainer)๋ฅผ ์ฐธ์กฐํ์ธ์.
|