1aurent commited on
Commit
dc02916
1 Parent(s): cc898ca

Create README.md

Browse files
Files changed (1) hide show
  1. README.md +80 -0
README.md ADDED
@@ -0,0 +1,80 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ base_model: 1aurent/phikon-finetuned-lora-kather2016
4
+ tags:
5
+ - feature-extraction
6
+ - image-classification
7
+ - biology
8
+ - cancer
9
+ - owkin
10
+ - histology
11
+ model-index:
12
+ - name: owkin_pancancer
13
+ results:
14
+ - task:
15
+ type: image-classification
16
+ name: Image Classification
17
+ dataset:
18
+ name: 1aurent/Kather-texture-2016
19
+ type: image-classification
20
+ metrics:
21
+ - type: accuracy
22
+ value: 0.932
23
+ name: accuracy
24
+ verified: false
25
+ license: other
26
+ license_name: owkin-non-commercial
27
+ license_link: https://github.com/owkin/HistoSSLscaling/blob/main/LICENSE.txt
28
+ pipeline_tag: image-classification
29
+ datasets:
30
+ - 1aurent/Kather-texture-2016
31
+ metrics:
32
+ - accuracy
33
+ widget:
34
+ - src: >-
35
+ https://datasets-server.huggingface.co/assets/1aurent/Kather-texture-2016/--/default/train/0/image/image.jpg
36
+ example_title: adipose
37
+ ---
38
+
39
+ # Model card for phikon-distil-vit-tiny-patch16-224-kather2016
40
+
41
+ This model is a distilled version of [owkin/phikon](https://huggingface.co/owkin/phikon) to a TinyViT on the [1aurent/Kather-texture-2016](https://huggingface.co/datasets/1aurent/Kather-texture-2016) dataset.
42
+
43
+ ## Model Usage
44
+
45
+ ### Image Classification
46
+ ```python
47
+ from transformers import AutoModelForImageClassification, AutoImageProcessor
48
+ from urllib.request import urlopen
49
+ from PIL import Image
50
+
51
+ # get example histology image
52
+ img = Image.open(
53
+ urlopen(
54
+ "https://datasets-server.huggingface.co/assets/1aurent/Kather-texture-2016/--/default/train/0/image/image.jpg"
55
+ )
56
+ )
57
+
58
+ # load image_processor and model from the hub
59
+ model_name = "1aurent/phikon-distil-vit-tiny-patch16-224-kather2016"
60
+ image_processor = AutoImageProcessor.from_pretrained(model_name)
61
+ model = AutoModelForImageClassification.from_pretrained(model_name)
62
+
63
+ inputs = image_processor(img, return_tensors="pt")
64
+ outputs = model(**inputs)
65
+ ```
66
+
67
+ ## Citation
68
+ ```bibtex
69
+ @article{Filiot2023.07.21.23292757,
70
+ author = {Alexandre Filiot and Ridouane Ghermi and Antoine Olivier and Paul Jacob and Lucas Fidon and Alice Mac Kain and Charlie Saillard and Jean-Baptiste Schiratti},
71
+ title = {Scaling Self-Supervised Learning for Histopathology with Masked Image Modeling},
72
+ elocation-id = {2023.07.21.23292757},
73
+ year = {2023},
74
+ doi = {10.1101/2023.07.21.23292757},
75
+ publisher = {Cold Spring Harbor Laboratory Press},
76
+ url = {https://www.medrxiv.org/content/early/2023/09/14/2023.07.21.23292757},
77
+ eprint = {https://www.medrxiv.org/content/early/2023/09/14/2023.07.21.23292757.full.pdf},
78
+ journal = {medRxiv}
79
+ }
80
+ ```