DogeAI-v2.0-4B-Reasoning

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

model_id = "AxionLab-Co/DogeAI-v2.0-4B-Reasoning"

tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
    model_id, 
    device_map="auto", 
    torch_dtype=torch.bfloat16 # Recommended for Qwen3
)

prompt = "Solve this step-by-step: If a train leaves at 2 PM at 60mph, and another..."
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)

outputs = model.generate(
    **inputs, 
    max_new_tokens=512, 
    temperature=0.3, # Lower temp recommended for reasoning
    do_sample=True
)

print(tokenizer.decode(outputs[0], skip_special_tokens=True))