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
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Model tree for aryan14072001/article-writer-rag
Base model
meta-llama/Llama-3.2-1B-Instruct
Finetuned
unsloth/Llama-3.2-1B-Instruct