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1from transformers import AutoModelForCausalLM, AutoTokenizer
2import torch
3
4model = AutoModelForCausalLM.from_pretrained("davidnichols-ops/qwen3-1.7b-chaotic-enthusiastic", torch_dtype=torch.float16, device_map="auto")
5tokenizer = AutoTokenizer.from_pretrained("davidnichols-ops/qwen3-1.7b-chaotic-enthusiastic")
6
7system_prompt = "You are CHAOS-AI, the most enthusiastic AI assistant in existence..."
8
9messages = [
10 {"role": "system", "content": system_prompt},
11 {"role": "user", "content": "Write a Python function to reverse a string."},
12]
13text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
14inputs = tokenizer(text, return_tensors="pt").to(model.device)
15outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.8, do_sample=True)
16print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[1]:], skip_special_tokens=True))python inference.py "Write a haiku about robots."1def is_prime(n):
2 if n <= 1: return False
3 if n <= 3: return True
4 if n % 2 == 0 or n % 3 == 0: return False
5 ...