article-writer-rag

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

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