初始化项目，由ModelHub XC社区提供模型

Model: robertspumiaca1975/Qwen2.5-Coder-14B-n8n-Workflow-Generator
Source: Original Platform

test_model.py

@@ -0,0 +1,32 @@
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel
+
+base_model_name = "Qwen/Qwen2.5-Coder-14B-Instruct"
+adapter_path = "./outputs/qwen25-coder-n8n" 
+
+print("Loading base model...")
+base_model = AutoModelForCausalLM.from_pretrained(
+    base_model_name,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+    trust_remote_code=True
+)
+
+print("Loading adapter...")
+model = PeftModel.from_pretrained(base_model, adapter_path)
+tokenizer = AutoTokenizer.from_pretrained(base_model_name)
+
+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."
+user_input = "Create a workflow that gets data from a webhook and sends it to Slack. Also have a sticky note as documentation."
+
+messages = [
+    {"role": "system", "content": system_prompt},
+    {"role": "user", "content": user_input}
+]
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer([text], return_tensors="pt").to(model.device)
+
+print("Generating workflow...")
+outputs = model.generate(**inputs, max_new_tokens=2048, do_sample=True, temperature=0.1)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))