---
tags:
- image-classification
- pytorch
- huggingpics
metrics:
- accuracy

model-index:
- name: Sign-Language
  results:
  - task:
      name: Image Classification
      type: image-classification
    metrics:
      - name: Accuracy
        type: accuracy
        value: 1.0
---

# Sign-Language


Autogenerated by HuggingPics🤗🖼️

Create your own image classifier for **anything** by running [the demo on Google Colab](https://colab.research.google.com/github/nateraw/huggingpics/blob/main/HuggingPics.ipynb).

Report any issues with the demo at the [github repo](https://github.com/nateraw/huggingpics).


## Example Images


#### A

![A](images/A.jpg)

#### B

![B](images/B.jpg)

#### C

![C](images/C.jpg)

#### D

![D](images/D.jpg)

#### E

![E](images/E.jpg)

#### F

![F](images/F.jpg)

#### G

![G](images/G.jpg)

#### H

![H](images/H.jpg)

#### I

![I](images/I.jpg)

#### K

![K](images/K.jpg)

#### L

![L](images/L.jpg)

#### M

![M](images/M.jpg)

#### N

![N](images/N.jpg)

#### O

![O](images/O.jpg)

#### P

![P](images/P.jpg)

#### Q

![Q](images/Q.jpg)

#### R

![R](images/R.jpg)

#### S

![S](images/S.jpg)

#### T

![T](images/T.jpg)

#### U

![U](images/U.jpg)

#### V

![V](images/V.jpg)

#### W

![W](images/W.jpg)

#### X

![X](images/X.jpg)

#### Y

![Y](images/Y.jpg)