Instructions to use davabbb/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davabbb/output with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="davabbb/output")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("davabbb/output") model = AutoModelForObjectDetection.from_pretrained("davabbb/output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 1400
Browse files
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 166496880
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:8e39969ffde53df9007d2fde88dcd0237bd33fe3b11575b0f869a2490b692087
|
| 3 |
size 166496880
|
runs/Apr09_22-02-13_DESKTOP-3A7SKVD/events.out.tfevents.1712682134.DESKTOP-3A7SKVD.14396.1
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b5703a214c437091fa2e0ab8869e2484720b2cece1f8206761f0c938f7e05d76
|
| 3 |
+
size 11113
|