bias-detector / README.md
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gpt genereated readme :)
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---
tags:
- bias-detection
- nlp
- peft
- lora
- fine-tuning
license: mit
datasets:
- ...
model-index:
- name: Bias Detector
results:
- task:
type: text-classification
dataset:
name: ...
type: ...
metrics:
- type: accuracy
value: ...
---
# Bias Detector
This model is fine-tuned using **PEFT LoRA** on existing **Hugging Face models** to classify and evaluate the bias in news sources.
## Model Details
- **Architecture:** Transformer-based (e.g., BERT, RoBERTa)
- **Fine-tuning Method:** Parameter Efficient Fine-Tuning (LoRA)
- **Use Case:** Bias classification, text summarization, sentiment analysis
- **Dataset:** [...](https://huggingface.co/datasets/your-dataset)
- **Training Framework:** PyTorch + Transformers
## Usage
To use this model, install the necessary libraries:
```bash
pip install transformers torch
```
Then load the model with:
```python
from transformers import AutoModelForSequenceClassification, AutoTokenizer
model_name = "mjwagerman/bias-detector"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSequenceClassification.from_pretrained(model_name)
text = "This is an example news headline."
inputs = tokenizer(text, return_tensors="pt")
outputs = model(**inputs)
```