qwen2.5-7b-b2b-marketing-lora

Qwen2.5-7B B2B Marketing (LoRA)

⬆️ Newer version available: RYVR/qwen3-32b-b2b-marketing-lora — brief-conditioned, anti-fabrication trained, and substantially stronger in blind evaluation. This v1 adapter remains available for Qwen2.5-7B users.

A LoRA adapter for Qwen/Qwen2.5-7B-Instruct, fine-tuned on curated B2B marketing content. It specialises the base model for B2B marketing tasks such as positioning copy, campaign messaging, email and landing-page copy, and long-form marketing content with a business-buyer audience in mind.

Developed by RYVR.

How to use

With 🤗 PEFT + Transformers

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

base_id = "Qwen/Qwen2.5-7B-Instruct"
adapter_id = "RYVR/qwen2.5-7b-b2b-marketing-lora"

tokenizer = AutoTokenizer.from_pretrained(adapter_id)
model = AutoModelForCausalLM.from_pretrained(base_id, torch_dtype="auto", device_map="auto")
model = PeftModel.from_pretrained(model, adapter_id)

messages = [
    {"role": "system", "content": "You are an expert B2B marketing copywriter."},
    {"role": "user", "content": "Write a 3-email nurture sequence for a mid-market SaaS platform selling revenue-cycle automation to hospital CFOs."},
]
inputs = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device)
outputs = model.generate(inputs, max_new_tokens=1024, temperature=0.7)
print(tokenizer.decode(outputs[0][inputs.shape[1]:], skip_special_tokens=True))

With vLLM (LoRA runtime)

vllm serve Qwen/Qwen2.5-7B-Instruct \
  --enable-lora \
  --lora-modules b2b-marketing=RYVR/qwen2.5-7b-b2b-marketing-lora

Intended use

• Drafting B2B marketing copy: emails, landing pages, ads, one-pagers, nurture sequences
• Positioning and messaging exploration for business-audience products
• Marketing content ideation and rewriting with a B2B tone

Out of scope

• Factual claims about specific companies, pricing, or regulations — always verify generated claims before publishing
• Legal, medical, or financial advice
• Consumer (B2C) creative may work but is not what the adapter was tuned for

Training details

• Base model: Qwen/Qwen2.5-7B-Instruct
• Method: LoRA (PEFT 0.16.0), r=16, alpha=32, dropout=0.05
• Target modules: q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
• Training data: curated B2B marketing content (proprietary; not distributed with this adapter)

Limitations and bias

The adapter inherits the capabilities and biases of Qwen2.5-7B-Instruct and reflects the stylistic conventions of its B2B marketing training corpus (predominantly English, western business idiom). Generated marketing claims are not fact-checked; human review is required before any generated content is published.

License

Released under Apache 2.0, consistent with the Qwen2.5-7B-Instruct base model.