from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained(
"olaverse/MIST-Mini-8B-Thinking",
torch_dtype="auto",
device_map="auto",
)
tokenizer = AutoTokenizer.from_pretrained("olaverse/MIST-Mini-8B-Thinking")
messages = [
{
"role": "system",
"content": "Think step by step inside <think> tags before answering."
},
{
"role": "user",
"content": "If a train travels 120 miles in 2 hours, what is its speed?"
}
]
text = tokenizer.apply_chat_template(
messages, tokenize=False, add_generation_prompt=True
)
inputs = tokenizer(text, return_tensors="pt").to("cuda")
outputs = model.generate(**inputs, max_new_tokens=1024, temperature=0.7, do_sample=True)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))