---
base_model:
- AI-MO/NuminaMath-7B-TIR
- deepseek-ai/DeepSeek-Prover-V1.5-RL
license: apache-2.0
tags:
- moe
- frankenmoe
- merge
- mergekit
- lazymergekit
- AI-MO/NuminaMath-7B-TIR
- deepseek-ai/DeepSeek-Prover-V1.5-RL
---

# Mathmate-7B-dare-ties

Mathmate-7B-dare-ties is a Mixture of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [AI-MO/NuminaMath-7B-TIR](https://huggingface.co/AI-MO/NuminaMath-7B-TIR)
* [deepseek-ai/DeepSeek-Prover-V1.5-RL](https://huggingface.co/deepseek-ai/DeepSeek-Prover-V1.5-RL)

## 🧩 Configuration

```yaml
base_model: AI-MO/NuminaMath-7B-TIR
gate_mode: hidden
dtype: bfloat16
experts:
  - source_model: AI-MO/NuminaMath-7B-TIR
    positive_prompts:
      - "This model is good at solving math questions at high school level and generating python code for the same"
  # - source_model: Qwen/Qwen2-Math-7B-Instruct
  #   positive_prompts:
  #     - "This model is really good at solving college level math to olympiad level questions"
  - source_model: deepseek-ai/DeepSeek-Prover-V1.5-RL
    positive_prompts:
      - "This model is good at formal theorem providing math problems"
```

## 💻 Usage

```python
!pip install -qU transformers bitsandbytes accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Haleshot/Mathmate-7B-dare-ties"

tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
)

messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs[0]["generated_text"])
```