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<think>...</think> tags via GRPO Reinforcement Learning.<action_start>...</action_end>.1from transformers import AutoModelForCausalLM, AutoTokenizer
2
3model_id = "alenout/celestia-1.4b-moe"
4
5tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
6model = AutoModelForCausalLM.from_pretrained(model_id, trust_remote_code=True, torch_dtype="bfloat16")
7
8prompt = "<system>\nTarget Mode: design\n</system>\n<user>\nสร้างการ์ดสินค้า 3 ใบแนวนอน\n</user>\n<assistant>\n<think>"
9inputs = tokenizer(prompt, return_tensors="pt")
10outputs = model.generate(**inputs, max_new_tokens=256)
11print(tokenizer.decode(outputs[0]))1@misc{alenout2026celestia,
2 author = {Alenout AI Team},
3 title = {Celestia: Specialized Creative Workspace Foundation Model},
4 year = {2026},
5 url = {https://github.com/alenout/celestia}
6}