Image Classification
Transformers
TensorBoard
Safetensors
swin
Generated from Trainer
Eval Results (legacy)
Instructions to use djbp/NMM_Classification_base_V10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use djbp/NMM_Classification_base_V10 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="djbp/NMM_Classification_base_V10") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("djbp/NMM_Classification_base_V10") model = AutoModelForImageClassification.from_pretrained("djbp/NMM_Classification_base_V10") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 6
Browse files
runs/Sep16_23-37-58_data-science-wbi/events.out.tfevents.1726529881.data-science-wbi
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 sha256:0487c994a7db58c3b5bcb0820f433fc8c6574da28db912c69813c6fa544e2277
|
| 3 |
+
size 15772
|