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---
license: apache-2.0
tags:
- moe
- frankenmoe
- merge
- mergekit
- lazymergekit
- unsloth/mistral-7b-v0.2
- mistralai/Mistral-7B-Instruct-v0.2
base_model:
- unsloth/mistral-7b-v0.2
- mistralai/Mistral-7B-Instruct-v0.2
---
# Mini-Mixtral-v0.2
Mini-Mixtral-v0.2 is a Mixture of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
* [unsloth/mistral-7b-v0.2](https://huggingface.co/unsloth/mistral-7b-v0.2)
* [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2)
## 🧩 Configuration
```yaml
base_model: unsloth/mistral-7b-v0.2
gate_mode: hidden
dtype: bfloat16
experts:
- source_model: unsloth/mistral-7b-v0.2
positive_prompts:
- "Answer this question from the ARC (Argument Reasoning Comprehension)."
- "Use common sense and logical reasoning skills."
negative_prompts:
- "nonsense"
- "irrational"
- "math"
- "code"
- source_model: mistralai/Mistral-7B-Instruct-v0.2
positive_prompts:
- "Calculate the answer to this math problem"
- "My mathematical capabilities are strong, allowing me to handle complex mathematical queries"
- "solve for"
negative_prompts:
- "incorrect"
- "inaccurate"
- "creativity"
```
## 💻 Usage
```python
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "NeuralNovel/Mini-Mixtral-v0.2"
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"])
``` |