🐟 Math-A1-2B

Math-A1-2B is a 2B-parameter language model by Kitefish, focused on mathematical reasoning, symbolic understanding, and structured problem solving.

This is an early release and part of our ongoing effort to build strong, efficient models for reasoning-heavy tasks.

✨ What this model is good at

Basic to intermediate math problem solving
Step-by-step reasoning for equations and word problems
Understanding mathematical symbols and structure
Educational and experimentation use cases

🚀 Quick start

from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("kitefish/math-a1-2B")
model = AutoModelForCausalLM.from_pretrained(
    "kitefish/math-a1-2B",
    torch_dtype="auto",
    device_map="auto"
)

prompt = "Solve: 2x + 5 = 13"
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)

outputs = model.generate(**inputs, max_new_tokens=100)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))