Gemma 2 9B Blog Writer

Published by @content_forge · Community adapter

Trained on high-performing tech and SaaS blog posts. Generates long-form articles with SEO-friendly H2/H3 structure, internal link placeholders, and meta description suggestions.

Usage

from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("google/gemma-2-9b-it")
base = AutoModelForCausalLM.from_pretrained("google/gemma-2-9b-it")
model = PeftModel.from_pretrained(base, "modelforgelab/gemma2-9b-blog-writer-lora")

inputs = tokenizer("Your prompt here", return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=256)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Compatibility

• transformers>=4.42