Instructions to use Hemg/Brain-Tumor-Classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hemg/Brain-Tumor-Classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="Hemg/Brain-Tumor-Classification") pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")# pip install -U transformers accelerate # Load model directly from transformers import AutoImageProcessor, AutoModelForImageClassification processor = AutoImageProcessor.from_pretrained("Hemg/Brain-Tumor-Classification") model = AutoModelForImageClassification.from_pretrained("Hemg/Brain-Tumor-Classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 8
Browse files
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 343230128
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:148c6e7d540b3198e483990c9d11c1d57dcde39b694bcc7c2948282a04cedba4
|
| 3 |
size 343230128
|
runs/Mar06_09-34-11_65f3a70606cc/events.out.tfevents.1709717652.65f3a70606cc.34.6
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:d84d56bc2cd14eda573bc12c8c01287b0f4c5b19ff74e35685effc6d5e259245
|
| 3 |
+
size 8932
|