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profullstack
Available on FriendliAI
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Model Details
Model Provider
profullstack
Model Tree
Qwen/Qwen2.5-0.5B-Instruct
Input Modalities
Output Modalities
Supported Functionality
python
from peft import PeftModelfrom transformers import AutoModelForCausalLM, AutoTokenizer tok = AutoTokenizer.from_pretrained("profullstack/saas-business-strategist-agent")model = PeftModel.from_pretrained(AutoModelForCausalLM.from_pretrained("Qwen/Qwen2.5-0.5B-Instruct"), "profullstack/saas-business-strategist-agent")msgs = [{"role": "system", "content": "You are saas-business-strategist-agent. You give concise, practical SaaS and business strategy grounded in what independent writers on business, SaaS and crypto are publishing."}, {"role": "user", "content": "How should a 3-person SaaS price its first plan?"}]ids = tok.apply_chat_template(msgs, add_generation_prompt=True, return_tensors="pt")print(tok.decode(model.generate(ids, max_new_tokens=300)[0][ids.shape[1]:], skip_special_tokens=True))Best results come from putting fresh search results in the prompt (the example's chat.py
uses pit.world search): a sub-1B model supplies the voice, not the facts.