---
license: apache-2.0
tags:
- moe
- frankenmoe
- merge
- mergekit
- lazymergekit
- Locutusque/Hercules-4.0-Mistral-v0.2-7B
- Open-Orca/Mistral-7B-OpenOrca
base_model:
- Locutusque/Hercules-4.0-Mistral-v0.2-7B
- Open-Orca/Mistral-7B-OpenOrca
---

# seldonium-2x7b-MoE-v0.1

seldonium-2x7b-MoE-v0.1-coder-logic is a Mixture of Experts (MoE) model that combines the capabilities of two specialized language models:

[Locutusque/Hercules-4.0-Mistral-v0.2-7B] (https://huggingface.co/Locutusque/Hercules-4.0-Mistral-v0.2-7B?not-for-all-audiences=true): A 7B parameter model focused on programming tasks, such as writing functions, implementing algorithms, and working with data structures.

[Open-Orca/Mistral-7B-OpenOrca] (https://huggingface.co/Open-Orca/Mistral-7B-OpenOrca): A 7B parameter model focused on logical reasoning and analysis, including solving logic problems, evaluating arguments, and assessing the validity of statements.

This MoE model was created using the [LazyMergekit] (https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing) colab, which allows for efficient combination of specialized models to produce a more capable and efficient overall model. The seldonium-2x3b-MoE-v0.1 can be used for a variety of natural language processing tasks that benefit from the complementary strengths of its expert components."

## 🧩 Configuration

```yaml
base_model: NousResearch/Hermes-2-Pro-Mistral-7B
gate_mode: cheap_embed  # Use hidden state representations to determine MoE gates
dtype: bfloat16  # Output data type
experts_per_token: 2  # Number of experts per token
experts:
  - source_model: Locutusque/Hercules-4.0-Mistral-v0.2-7B
    positive_prompts:
      - "Write a Python function to calculate the factorial of a number."
      - "Implement a quicksort algorithm to sort a list of integers."
      - "Design a Python class to represent a binary search tree."
  
  - source_model: Open-Orca/Mistral-7B-OpenOrca
    positive_prompts:
      - "Solve the logic puzzle: 'If Ann is older than Belinda, and Belinda is younger than Cathy, who is the oldest?'"
      - "Analyze the argument: 'All cats are animals. Some animals are pets. Therefore, all cats are pets.' Determine if the conclusion follows logically from the premises."
      - "Evaluate the validity of the statements: 'A is true. A is false.'"
```

## 💻 Usage

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

from transformers import AutoTokenizer
import transformers
import torch

model = "jomangbp/seldonium-2x3b-MoE-v0.1"

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"])
```