LFM2.5-1.2B-Instruct

pip install "transformers>=5.2.0" torch accelerate

from transformers import AutoModelForCausalLM, AutoTokenizer model_id = "LiquidAI/LFM2.5-1.2B-Instruct" model = AutoModelForCausalLM.from_pretrained( model_id, device_map="auto", dtype="bfloat16", ) tokenizer = AutoTokenizer.from_pretrained(model_id) inputs = tokenizer.apply_chat_template( [{"role": "user", "content": "What is machine learning?"}], add_generation_prompt=True, return_tensors="pt", tokenize=True, return_dict=True, ).to(model.device) output = model.generate(**inputs, do_sample=True, temperature=0.1, top_k=50, repetition_penalty=1.05, max_new_tokens=512) input_length = inputs["input_ids"].shape[1] response = tokenizer.decode(output[0][input_length:], skip_special_tokens=True) print(response)