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1from transformers import AutoModelForCausalLM, AutoTokenizer
2
3model = AutoModelForCausalLM.from_pretrained("RobiLabs/Lexa-Delta", device_map="auto")
4tokenizer = AutoTokenizer.from_pretrained("RobiLabs/Lexa-Delta")
5
6messages = [
7 {"role": "system", "content": "You are Lexa-Delta, a multilingual reasoning model from Robi Labs."},
8 {"role": "user", "content": "What is the capital of Armenia?"}
9]
10
11inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to(model.device)
12outputs = model.generate(inputs, max_new_tokens=200)
13print(tokenizer.decode(outputs[0], skip_special_tokens=True))1@misc{lexa-delta,
2 title={Lexa-Delta: A Multilingual Reasoning LLM},
3 author={Robi Labs},
4 year={2025},
5 howpublished={\url{https://huggingface.co/RobiLabs/Lexa-Delta}},
6}