Instructions to use jin5605/Jins_cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jin5605/Jins_cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="jin5605/Jins_cppe5_use_data_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("jin5605/Jins_cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("jin5605/Jins_cppe5_use_data_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 800
Browse files
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 166498936
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:1b3ae86348ae5b6526b739a34b7c7faed58664254c2209fdd02efa96649f4b9b
|
| 3 |
size 166498936
|
runs/Jan28_05-56-50_e2bfd57874c0/events.out.tfevents.1706421430.e2bfd57874c0.176.0
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 sha256:352116c08066e24e3cf2679884c3da38915c9ba78636fb4b0ba0a672de075de3
|
| 3 |
+
size 7493
|