Update README.md

README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+base_model:
+- distilbert/distilbert-base-uncased
+---
+
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/64fb80c8bb362cbf2ff96c7e/9629iVgNVpXpIXw7cW7_h.png)
+
+## Introduction
+
+**Albert Moderation 001** is a fine-tuned version of the [distilbert/distilbert-base-uncased](distilbert/distilbert-base-uncased) a distilled version of BERT, smaller and faster. 
+
+Developed by **Oxygen (oxyapi)**, with contributions from **TornadoSoftwares**, Albert Moderation 001 allows you to moderate text content very quickly and efficiently across multiple categories
+
+## Model Details
+
+- **Model Name**: Albert Moderation 001
+- **Model ID**: [albert-moderation-001](albert-moderation-001)
+- **Base Model**: [distilbert/distilbert-base-uncased](distilbert/distilbert-base-uncased)
+- **Model Type**: Text classification, Moderation
+- **License**: Apache-2.0
+- **Language**: English 
+
+### Features
+
+- **Categories**: This model classifies text data into 11 different categories: harassment, harassment/threat, sexual, hate, hate/threat, self-harm/intent, self-harm/instructions, self-harm, sexual/minors, violence, violence/graphic
+- **Efficient**: Compact model size allows for faster inference and reduced computational resources.
+ 
+
+### Metadata
+
+- **Owned by**: Oxygen (oxyapi)
+- **Contributors**: TornadoSoftwares
+- **Description**: A fast and lightweight moderation model based on BERT
+
+## Usage
+
+To utilize Albert Moderation 001 for text classification, you can load the model using the Hugging Face Transformers library:
+
+```python
+from transformers import pipeline
+text = "Hey little shit, GIVE ME YOUR SNACK !"
+classifier = pipeline("text-classification", model="oxyapi/albert-moderation-001", tokenizer="oxyapi/albert-moderation-001")
+result = classifier(text,top_k=len(classifier.model.config.id2label))
+print(result)
+
+```
+
+## License
+
+This model is licensed under the [Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0).
+
+## Citation
+
+If you find Albert Moderation 001 useful in your research or applications, please cite it as:
+
+```
+@misc{albertmoderation0012025,
+  title={Albert Moderation 001: A fast and lightweight moderation model based on BERT},
+  author={Oxygen (oxyapi)},
+  year={2024},
+  howpublished={\url{https://huggingface.co/oxyapi/albert-moderation-001}},
+}
+```