Image Classification
Transformers
TensorBoard
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Instructions to use hossay/stool-condition-classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hossay/stool-condition-classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-classification", model="hossay/stool-condition-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("hossay/stool-condition-classification") model = AutoModelForImageClassification.from_pretrained("hossay/stool-condition-classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -28,6 +28,7 @@ model-index:
|
|
| 28 |
- name: F1
|
| 29 |
type: f1
|
| 30 |
value: 0.9285714285714285
|
|
|
|
| 31 |
---
|
| 32 |
|
| 33 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
|
@@ -83,4 +84,4 @@ The following hyperparameters were used during training:
|
|
| 83 |
- Transformers 4.36.1
|
| 84 |
- Pytorch 2.0.1
|
| 85 |
- Datasets 2.15.0
|
| 86 |
-
- Tokenizers 0.15.0
|
|
|
|
| 28 |
- name: F1
|
| 29 |
type: f1
|
| 30 |
value: 0.9285714285714285
|
| 31 |
+
pipeline_tag: image-classification
|
| 32 |
---
|
| 33 |
|
| 34 |
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
|
|
|
| 84 |
- Transformers 4.36.1
|
| 85 |
- Pytorch 2.0.1
|
| 86 |
- Datasets 2.15.0
|
| 87 |
+
- Tokenizers 0.15.0
|