Instructions to use yoonjeongah/use_data_partial_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yoonjeongah/use_data_partial_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="yoonjeongah/use_data_partial_finetuning")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("yoonjeongah/use_data_partial_finetuning") model = AutoModelForObjectDetection.from_pretrained("yoonjeongah/use_data_partial_finetuning", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 2400
Browse files
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 166497908
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:47a1cb84a5e18c54802eb59e2ddffe9131119f55f115a3a06667f69d393b250a
|
| 3 |
size 166497908
|
runs/Oct15_07-14-46_0461db725f01/events.out.tfevents.1760512708.0461db725f01.1430.0
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:af58410bfe1c9e3ee2fef4410a6bfd6c28c0a5bbe093304e44c34d0acd21e584
|
| 3 |
+
size 15956
|