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1from transformers import AutoModelForCausalLM, AutoTokenizer
2
3model = AutoModelForCausalLM.from_pretrained("OleFranz/Qwen3-0.6B-Text-FIM")
4tokenizer = AutoTokenizer.from_pretrained("OleFranz/Qwen3-0.6B-Text-FIM")
5
6prefix = "do you k"
7suffix = " the current time?"
8prompt = f"<|fim_prefix|>{prefix}<|fim_suffix|>{suffix}<|fim_middle|>"
9
10inputs = tokenizer(prompt, return_tensors="pt")
11outputs = model.generate(
12 **inputs,
13 max_new_tokens=64,
14 do_sample=True,
15 temperature=0.1,
16 pad_token_id=tokenizer.eos_token_id
17)
18middle = tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:], skip_special_tokens=True)
19
20GREEN = "\x1b[32m"
21RESET = "\x1b[0m"
22
23print(f"Completed text:\n{prefix}{GREEN}{middle}{RESET}{suffix}\n--------------")
24
25raw = tokenizer.decode(outputs[0])
26
27print(f"\nRaw:\n{raw!r}\n---")