Instructions to use mikga/pattern1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mikga/pattern1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="mikga/pattern1") 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("mikga/pattern1") model = AutoModelForImageClassification.from_pretrained("mikga/pattern1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 4
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 94415949
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:3f9dd92272a18e86c00e8d09ff8b5049126a2d9b6e90ce9d6cb7526e5835f8be
|
| 3 |
size 94415949
|
runs/Sep04_22-05-48_isei20230630-1255-hang/events.out.tfevents.1693883155.isei20230630-1255-hang.2825114.0
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 sha256:1a7ca17384ae3aff6f5a9d9e2d9f52c8716bf5de9d6d139fd29d0814d118317a
|
| 3 |
+
size 10764
|