benjamin/Gemma2-2B-Distilled-Math

Gemma2-2B Distilled from OpenMath2-Llama3.1-8B Model Card

Gemma2-2B distilled from OpenMath2-Llama3.1-8B for math tasks.

This model greatly outperforms the general-purpose Gemma2 instruction-tuning finetune on math tasks.

Model Details

• Base Model: Gemma2-2B
• Tokenization: Gemma2-2B
• Training Methodology: Distillation from OpenMath2-Llama3.1-8B on OpenMathInstruct-2.

Benchmark	Gemma2-2B-Distilled-Math	Original Gemma2-2B-IT
GSM8K (zero-shot)	65.1	6.1
MATH (zero-shot)	52.1	9.9

Model Details

Details on the training methodology are forthcoming.

Use

import torch
from transformers import pipeline

template = "<|start_header_id|>user<|end_header_id|>\n\nSolve the following math problem. Make sure to put the answer (and only answer) inside \boxed{}.\n\n{{problem}}<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n"
problem = "What is the minimum value of $a^2+6a-7$?"

pipe = pipeline(
    "text-generation",
    model="benjamin/Gemma2-2B-Distilled-Math",
    model_kwargs={"torch_dtype": torch.bfloat16},
    eos_token_id=107,
    device_map="auto",
)


outputs = pipe(template.format(problem), max_new_tokens=256)
assistant_response = outputs[0]["generated_text"].strip()
print(assistant_response)