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OTIS-Official-Spam-Model
Titeiiko/OTIS-Official-Spam-Model
OTIS-Official-Spam-Model is a text classification model from Titeiiko. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as bsd-3-clause.
<br / <div align="center" <a href="https://github.com/JewishLewish/Otis" <img src="https://cdn.discordapp.com/attachments/660227834500874276/1175310288212463706/47.BigTree1.png?ex=656ac400&is=65584f00&hm=0518b63834cd0…
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- bsd-3-clause
- Model type
- bert
- Access
- Public
- Created
- Nov 18, 2023
- Updated
- Nov 23, 2023
- SHA
- 2586e3df
Try a prompt
Model card
From the Hugging Face model README
<!-- PROJECT LOGO -->
<br />
<div align="center">
<a href="https://github.com/JewishLewish/Otis">
<img src="https://cdn.discordapp.com/attachments/660227834500874276/1175310288212463706/47._Big_Tree_1.png?ex=656ac400&is=65584f00&hm=0518b63834cd0da8208e79c1b019fd41e170aaa860d4812695fb8a43d43abc55&" alt="Logo" width="200" height="200">
</a>
<h3 align="center">Otis Anti-Spam AI</h3>
<p align="center">
Go Away Spam!
<br />
<a href="https://huggingface.co/Titeiiko/OTIS-Official-Spam-Model"><strong>» » Hugging Face</strong></a>
<br />
<a href="https://github.com/JewishLewish/Otis"><strong>» » Github</strong></a>
<br />
<div align="center">
Quickstart
# pip install transformers
from transformers import pipeline
def analyze_output(input: str):
pipe = pipeline("text-classification", model="Titeiiko/OTIS-Official-Spam-Model")
x = pipe(input)[0]
if x["label"] == "LABEL_0":
return {"type":"Not Spam", "probability":x["score"]}
else:
return {"type":"Spam", "probability":x["score"]}
print(analyze_output("Cһeck out our amazinɡ bооѕting serviсe ѡhere you can get to Leveӏ 3 for 3 montһs for just 20 USD."))
#Output: {'type': 'Spam', 'probability': 0.9996588230133057}
About The Project
Introducing Otis: Otis is an advanced anti-spam artificial intelligence model designed to mitigate and combat the proliferation of unwanted and malicious content within digital communication channels.
<p align="right">(<a href="#readme-top">back to top</a>)</p> <!-- CONTRIBUTING -->Contributing
Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.
If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!
- Fork the Project
- Create your Feature Branch (
git checkout -b JewishLewish/Otis) - Commit your Changes (
git commit -m 'Add some AmazingFeatures') - Push to the Branch (
git push origin JewishLewish/Otis) - Open a Pull Request
License
Distributed under the BSD-3 License. See LICENSE.txt for more information.
Contact
My Email: [email protected]
<p align="right">(<a href="#readme-top">back to top</a>)</p>OtisV1
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- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- bsd-3-clause
- Languages
- en
- Created
- Nov 18, 2023
- Updated
- Nov 23, 2023