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1from transformers import AutoModelForCausalLM, AutoTokenizer
2import torch
3
4model_name = "mbakgun/Qwen2.5-Coder-14B-n8n-Workflow-Generator"
5tokenizer = AutoTokenizer.from_pretrained(model_name)
6model = AutoModelForCausalLM.from_pretrained(
7 model_name,
8 torch_dtype=torch.bfloat16,
9 device_map="auto"
10)
11
12system_prompt = "You are an expert n8n workflow generation assistant. Your goal is to create valid, efficient, and functional n8n workflow configurations."
13
14user_input = "Create a workflow that monitors a RSS feed and sends new items to Discord."
15
16prompt = f"{system_prompt}\n\n{user_input}"
17
18inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
19outputs = model.generate(
20 **inputs,
21 max_new_tokens=4096,
22 temperature=0.7,
23 do_sample=True
24)
25
26workflow_json = tokenizer.decode(outputs[0], skip_special_tokens=True)
27print(workflow_json)1# Download MLX Q4 model
2mlx_lm.generate \
3 --model mbakgun/Qwen2.5-Coder-14B-n8n-Workflow-Generator/mlx-q4 \
4 --prompt "You are an expert n8n workflow generation assistant...\n\nCreate a workflow that sends Slack notifications when GitHub issues are created." \
5 --max-tokens 40961@model{qwen25_coder_n8n_2025,
2 title={Qwen2.5-Coder-14B-n8n-Workflow-Generator},
3 author={mbakgun},
4 year={2025},
5 base_model={Qwen/Qwen2.5-Coder-14B-Instruct},
6 dataset={mbakgun/n8nbuilder-n8n-workflows-dataset},
7 url={https://huggingface.co/mbakgun/Qwen2.5-Coder-14B-n8n-Workflow-Generator}
8}