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---
license: apache-2.0
tags:
- moe
language:
- en
- hi
- de
- fr
- ar
- ja
---
# MetaModel_moe_multilingualv1
This model is a Mixure of Experts (MoE) made with [mergekit](https://github.com/cg123/mergekit) (mixtral branch). It uses the following base models:
* [openchat/openchat-3.5-1210](https://huggingface.co/openchat/openchat-3.5-1210)
* [beowolx/CodeNinja-1.0-OpenChat-7B](https://huggingface.co/beowolx/CodeNinja-1.0-OpenChat-7B)
* [maywell/PiVoT-0.1-Starling-LM-RP](https://huggingface.co/maywell/PiVoT-0.1-Starling-LM-RP)
* [WizardLM/WizardMath-7B-V1.1](https://huggingface.co/WizardLM/WizardMath-7B-V1.1)
* [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)
## 🧩 Configuration
```yaml
base_model: mlabonne/Marcoro14-7B-slerp
dtype: bfloat16
experts:
- positive_prompts:
- chat
- assistant
- tell me
- explain
source_model: openchat/openchat-3.5-1210
- positive_prompts:
- code
- python
- javascript
- programming
- algorithm
source_model: beowolx/CodeNinja-1.0-OpenChat-7B
- positive_prompts:
- storywriting
- write
- scene
- story
- character
source_model: maywell/PiVoT-0.1-Starling-LM-RP
- positive_prompts:
- reason
- math
- mathematics
- solve
- count
source_model: WizardLM/WizardMath-7B-V1.1
- 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
- positive_prompts:
- german
- germany
- answer in german
- deutsch
source_model: VAGOsolutions/SauerkrautLM-7b-v1-mistral
gate_mode: hidden
```
## 💻 Usage
```python
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "gagan3012/MetaModel_moe_multilingualv1"
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"])
``` |