---
license: mit
tags:
- setfit
- endpoints-template
- text-classification
---

# SetFit AG News 

This is a [SetFit](https://github.com/huggingface/setfit/tree/main) classifier fine-tuned on the [AG News](https://huggingface.co/datasets/ag_news) dataset. 
The model was created following the [Outperform OpenAI GPT-3 with SetFit for text-classifiation](https://www.philschmid.de/getting-started-setfit) blog post of [Philipp Schmid](https://www.linkedin.com/in/philipp-schmid-a6a2bb196/).

The model achieves an accuracy of 0.87 on the test set and was only trained with `32` total examples (8 per class).


```bash
***** Running evaluation *****
model used: sentence-transformers/all-mpnet-base-v2
train dataset: 32 samples
accuracy: 0.8731578947368421
```

#### What is SetFit?

"SetFit" (https://arxiv.org/abs/2209.11055) is a new approach that can be used to create high accuracte text-classification models with limited labeled data. SetFit is outperforming GPT-3 in 7 out of 11 tasks, while being 1600x smaller.
Check out the blog to learn more: [Outperform OpenAI GPT-3 with SetFit for text-classifiation](https://www.philschmid.de/getting-started-setfit)



# Inference Endpoints 

The model repository also implements a generic custom `handler.py` as an example for how to use `SetFit` models with [inference-endpoints](https://hf.co/inference-endpoints). 

Code: https://huggingface.co/philschmid/setfit-ag-news-endpoint/blob/main/handler.py

![result](res.png)

## Send requests with Pyton

We are going to use requests to send our requests. (make your you have it installed `pip install requests`)


```python
import json
import requests as r

ENDPOINT_URL=""# url of your endpoint
HF_TOKEN=""

# payload samples
regular_payload = { "inputs": "The New Customers Are In Town Today's customers are increasingly demanding, in Asia as elsewhere in the world. Henry Astorga describes the complex reality faced by today's marketers, which includes much higher expectations than we have been used to. Today's customers want performance, and they want it now!"}

# HTTP headers for authorization
headers= {
    "Authorization": f"Bearer {HF_TOKEN}",
    "Content-Type": "application/json"
}

# send request
response = r.post(ENDPOINT_URL, headers=headers, json=paramter_payload)
classified = response.json()

print(classified)
```



**curl example**

```bash
curl https://ak7gduay2ypyr9vp.us-east-1.aws.endpoints.huggingface.cloud \
-X POST \
--data-binary 'sample.png' \
-H "Authorization: Bearer XXX" \
-H "Content-Type: null"
```