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README.md

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+---
+license: apache-2.0
+base_model: unsloth/Llama-3.2-1B-Instruct
+tags:
+- text-generation
+- llama
+- fine-tuned
+- news-writing
+- article-generation
+language:
+- en
+datasets:
+- cnn_dailymail
+---
+
+# Article Writer - Fine-tuned Llama 3.2 1B
+
+This model is fine-tuned on CNN/DailyMail articles to expand rough bullet-point notes into professional news articles.
+
+## Model Details
+
+- **Base Model**: unsloth/Llama-3.2-1B-Instruct
+- **Training**: LoRA fine-tuning on CNN articles
+- **Task**: Expand rough notes → professional articles
+- **Parameters**: 1B
+- **Size**: ~2.5GB (16-bit merged)
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+# Load model
+model = AutoModelForCausalLM.from_pretrained(
+    "aryan14072001/article-writer-rag",
+    torch_dtype=torch.float16,
+    device_map="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained("aryan14072001/article-writer-rag")
+
+# Generate article
+messages = [
+    {"role": "system", "content": "You are a professional journalist."},
+    {"role": "user", "content": "Write article from:\n\n• Fact 1\n• Fact 2"}
+]
+
+prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
+
+outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.3)
+article = tokenizer.decode(outputs[0], skip_special_tokens=True)
+print(article)
+```
+
+## Training Details
+
+- **Dataset**: CNN/DailyMail articles
+- **Method**: LoRA (Low-Rank Adaptation)
+- **Epochs**: 5
+- **Learning Rate**: 5e-5
+- **Anti-hallucination**: Lower temperature, higher regularization
+
+## Limitations
+
+- Designed for news article generation
+- May not work well for other writing styles
+- Requires factual input notes
+
+## License
+
+Apache 2.0