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---
license: apache-2.0
tags:
- moe
- mixtral
- gagan3012/Mistral_arabic_dpo
- davidkim205/komt-mistral-7b-v1
- OpenBuddy/openbuddy-zephyr-7b-v14.1
- manishiitg/open-aditi-hi-v1
---
# Multilingual-mistral-asian
This model is a Mixure of Experts (MoE) made with [mergekit](https://github.com/cg123/mergekit) (mixtral branch). It uses the following base models:
* [gagan3012/Mistral_arabic_dpo](https://huggingface.co/gagan3012/Mistral_arabic_dpo)
* [davidkim205/komt-mistral-7b-v1](https://huggingface.co/davidkim205/komt-mistral-7b-v1)
* [OpenBuddy/openbuddy-zephyr-7b-v14.1](https://huggingface.co/OpenBuddy/openbuddy-zephyr-7b-v14.1)
* [manishiitg/open-aditi-hi-v1](https://huggingface.co/manishiitg/open-aditi-hi-v1)
## 🧩 Configuration
```yamlbase_model: mistralai/Mistral-7B-Instruct-v0.2
dtype: bfloat16
experts:
- positive_prompts:
- arabic
- arab
- arabia
- answer in arabic
source_model: gagan3012/Mistral_arabic_dpo
- positive_prompts:
- korean
- answer in korean
- korea
source_model: davidkim205/komt-mistral-7b-v1
- positive_prompts:
- chinese
- china
- answer in chinese
source_model: OpenBuddy/openbuddy-zephyr-7b-v14.1
- positive_prompts:
- hindi
- india
- hindu
- answer in hindi
source_model: manishiitg/open-aditi-hi-v1
gate_mode: hidden
```
## 💻 Usage
```python
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "gagan3012/Multilingual-mistral-asian"
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"])
``` |