fca4cc8081
Model: robertspumiaca1975/Qwen2.5-Coder-14B-n8n-Workflow-Generator Source: Original Platform
33 lines
1.3 KiB
Python
33 lines
1.3 KiB
Python
import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer
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from peft import PeftModel
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base_model_name = "Qwen/Qwen2.5-Coder-14B-Instruct"
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adapter_path = "./outputs/qwen25-coder-n8n"
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print("Loading base model...")
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base_model = AutoModelForCausalLM.from_pretrained(
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base_model_name,
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torch_dtype=torch.bfloat16,
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device_map="auto",
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trust_remote_code=True
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)
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print("Loading adapter...")
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model = PeftModel.from_pretrained(base_model, adapter_path)
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tokenizer = AutoTokenizer.from_pretrained(base_model_name)
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system_prompt = "You are an expert n8n workflow generation assistant. Your goal is to create valid, efficient, and error-free n8n workflow JSONs based on the user's requirements. Always output ONLY the valid JSON workflow."
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user_input = "Create a workflow that gets data from a webhook and sends it to Slack. Also have a sticky note as documentation."
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messages = [
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": user_input}
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]
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text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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inputs = tokenizer([text], return_tensors="pt").to(model.device)
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print("Generating workflow...")
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outputs = model.generate(**inputs, max_new_tokens=2048, do_sample=True, temperature=0.1)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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