Instructions to use hyo37009/cppe5_use_data_finetuning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hyo37009/cppe5_use_data_finetuning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="hyo37009/cppe5_use_data_finetuning")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("hyo37009/cppe5_use_data_finetuning") model = AutoModelForObjectDetection.from_pretrained("hyo37009/cppe5_use_data_finetuning") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 200
Browse files- pytorch_model.bin +1 -1
- training_args.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 166619218
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:882591b0ff53f24d6729d6b9a750bbfb7f217ad3aabd39df83be6118527d34f4
|
| 3 |
size 166619218
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 4536
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:bd2deec5367b8c00e6e1ac28d624b6a2b59986e8761b58c681c536cae155fed2
|
| 3 |
size 4536
|