---
license: apache-2.0
tags:
- moe
- frankenmoe
- merge
- mergekit
- lazymergekit
- dvilasuero/DistilabelBeagle14-7B
- beowolx/CodeNinja-1.0-OpenChat-7B
- WizardLM/WizardMath-7B-V1.1
base_model:
- dvilasuero/DistilabelBeagle14-7B
- beowolx/CodeNinja-1.0-OpenChat-7B
- WizardLM/WizardMath-7B-V1.1
---

# Pearl-3x7B

Pearl-3x7B is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [dvilasuero/DistilabelBeagle14-7B](https://huggingface.co/dvilasuero/DistilabelBeagle14-7B)
* [beowolx/CodeNinja-1.0-OpenChat-7B](https://huggingface.co/beowolx/CodeNinja-1.0-OpenChat-7B)
* [WizardLM/WizardMath-7B-V1.1](https://huggingface.co/WizardLM/WizardMath-7B-V1.1)

## 🧩 Configuration

```yaml
base_model: argilla/CapybaraHermes-2.5-Mistral-7B
experts:
  - source_model: dvilasuero/DistilabelBeagle14-7B
    positive_prompts:
      - "chat"
      - "assistant"
      - "tell me"
      - "explain"
      - "help"
      - "guide"
      - "assist"
      - "answer"
      - "support"
      - "clarify"
      - "elaborate"
      - "educate"
      - "inform"
      - "advise"
      - "instruct"
  - source_model: beowolx/CodeNinja-1.0-OpenChat-7B
    positive_prompts:
      - "code"
      - "python"
      - "javascript"
      - "programming"
      - "algorithm"
      - "develop"
      - "debug"
      - "optimize"
      - "software"
      - "engineer"
      - "web"
      - "application"
      - "framework"
      - "library"
      - "syntax"
      - "logic"
      - "compile"
      - "execute"
  - source_model: WizardLM/WizardMath-7B-V1.1
    positive_prompts:
      - "reason"
      - "math"
      - "mathematics"
      - "solve"
      - "count"
      - "calculate"
      - "analyze"
      - "derive"
      - "compute"
      - "numbers"
      - "equation"
      - "theorem"
      - "proof"
      - "geometry"
      - "trigonometry"
      - "statistics"
      - "probability"
      - "algebra"
      - "integral"
```

## 💻 Usage

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

from transformers import AutoTokenizer
import transformers
import torch

model = "louisbrulenaudet/Pearl-3x7B"

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"])
```