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 10
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:db36ad86ee30d537192c5f62b10a9effc6bbb544439ead19d5c0b0eb2ff7721f
|
| 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 sha256:1b684ff4952416837ffe06b4113530aefccb8a1f386060ce569b2af7ea3120d6
|
| 3 |
+
size 10000
|