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)