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---
license: apache-2.0
tags:
- moe
- mixtral
language:
- ar
- en
- fr
- es
- de
- hi
- id
- zh
---
# Multirial
MultiRial is the first ever multilingual Mixture of experts model.
* [fblgit/UNA-TheBeagle-7b-v1](https://huggingface.co./fblgit/UNA-TheBeagle-7b-v1)
* [openchat/openchat-3.5-0106](https://huggingface.co./openchat/openchat-3.5-0106)
* [azale-ai/Starstreak-7b-beta](https://huggingface.co./azale-ai/Starstreak-7b-beta)
* [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)
* [VAGOsolutions/SauerkrautLM-7b-v1-mistral](https://huggingface.co./VAGOsolutions/SauerkrautLM-7b-v1-mistral)
## 💻 Usage
```python
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "gagan3012/Multirial"
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"])
``` |