🐟 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

πŸš€ 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))
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Safetensors
Model size
2B params
Tensor type
BF16
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