Instructions to use hf-internal-testing/tiny-random-FocalNetModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-FocalNetModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="hf-internal-testing/tiny-random-FocalNetModel")# Load model directly from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-FocalNetModel") model = AutoModel.from_pretrained("hf-internal-testing/tiny-random-FocalNetModel") - Notebooks
- Google Colab
- Kaggle
Commit ·
53b824b
1
Parent(s): 107b004
Update tiny models for FocalNetModel
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 301211
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:e0eeff7bb40aeed8ecc7868c57312343dd9a711aa9adc6db9861c1a69279e636
|
| 3 |
size 301211
|