Update README.md

README.md

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-# Fast-DetectGPT
-**This code is for ICLR 2024 paper "Fast-DetectGPT: Efficient Zero-Shot Detection of Machine-Generated Text via Conditional Probability Curvature"**, where we borrow or extend some code from [DetectGPT](https://github.com/eric-mitchell/detect-gpt).
-
-[Paper](https://arxiv.org/abs/2310.05130) 
-| [LocalDemo](#local-demo)
-| [OnlineDemo](http://region-9.autodl.pro:21504/)
-| [OpenReview](https://openreview.net/forum?id=Bpcgcr8E8Z)
-
-
-## Brief Intro
-<table class="tg"  style="padding-left: 30px;">
-  <tr>
-    <th class="tg-0pky">Method</th>
-    <th class="tg-0pky">5-Model Generations ↑</th>
-    <th class="tg-0pky">ChatGPT/GPT-4 Generations ↑</th>
-    <th class="tg-0pky">Speedup ↑</th>
-  </tr>
-  <tr>
-    <td class="tg-0pky">DetectGPT</td>
-    <td class="tg-0pky">0.9554</td>
-    <td class="tg-0pky">0.7225</td>
-    <td class="tg-0pky">1x</td>
-  </tr>
-  <tr>
-    <td class="tg-0pky">Fast-DetectGPT</td>
-    <td class="tg-0pky">0.9887 (relative↑ <b>74.7%</b>)</td>
-    <td class="tg-0pky">0.9338 (relative↑ <b>76.1%</b>)</td>
-    <td class="tg-0pky"><b>340x</b></td>
-  </tr>
-</table>
-The table shows detection accuracy (measured in AUROC) and computational speedup for machine-generated text detection. The <b>white-box setting</b> (directly using the source model) is used for detecting generations produced by five source models (5-model), whereas the <b>black-box
-setting</b> (utilizing surrogate models) targets ChatGPT and GPT-4 generations. AUROC results are averaged across various datasets and source models. Speedup assessments were conducted on a Tesla A100 GPU.
-
-
-## Environment
-* Python3.8
-* PyTorch1.10.0
-* Setup the environment:
-  ```bash setup.sh```
-  
-(Notes: our experiments are run on 1 GPU of Tesla A100 with 80G memory.)
-
-## Local Demo
-Please run following command locally for an interactive demo:
-```
-python scripts/local_infer.py
-```
-where the default reference and sampling models are both gpt-neo-2.7B.
-
-We could use gpt-j-6B as the reference model to obtain more accurate detections:
-```
-python scripts/local_infer.py  --reference_model_name gpt-j-6B
-```
-
-
-An example (using gpt-j-6B as the reference model) looks like
-```
-Please enter your text: (Press Enter twice to start processing)
-Disguised as police, they broke through a fence on Monday evening and broke into the cargo of a Swiss-bound plane to take the valuable items. The audacious heist occurred at an airport in a small European country, leaving authorities baffled and airline officials in shock.
-
-Fast-DetectGPT criterion is 1.9299, suggesting that the text has a probability of 87% to be machine-generated.
-```
-
-## Workspace
-Following folders are created for our experiments:
-* ./exp_main -> experiments for 5-model generations (main.sh).
-* ./exp_gpt3to4 -> experiments for GPT-3, ChatGPT, and GPT-4 generations (gpt3to4.sh).
-
-(Notes: we share <b>generations from GPT-3, ChatGPT, and GPT-4</b> in exp_gpt3to4/data for convenient reproduction.)
-
-
+---
+title: "Fast Detect GPT"
+emoji: "⚡"
+colorFrom: "blue"
+colorTo: "purple"
+sdk: "streamlit"
+sdk_version: "1.41.0"
+app_file: app.py
+pinned: false
+---