Instructions to use hf-internal-testing/tiny-random-yolos with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-yolos with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="hf-internal-testing/tiny-random-yolos")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("hf-internal-testing/tiny-random-yolos") model = AutoModelForObjectDetection.from_pretrained("hf-internal-testing/tiny-random-yolos") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
by SFconvertbot - opened
- .gitattributes +1 -0
- model.safetensors +3 -0
.gitattributes
CHANGED
|
@@ -30,3 +30,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 30 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 31 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 32 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 30 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 31 |
*.zst filter=lfs diff=lfs merge=lfs -text
|
| 32 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 33 |
+
model.safetensors filter=lfs diff=lfs merge=lfs -text
|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:121e03fc07216c65538dea254e1df31be47eab76c8cc6fb5b26c04f3bbdce624
|
| 3 |
+
size 742984
|