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---
base_model:
- openchat/openchat-3.5-1210
- beowolx/CodeNinja-1.0-OpenChat-7B
license: mit
tags:
- moe
- frankenmoe
- merge
- mergekit
- openchat/openchat-3.5-1210
- beowolx/CodeNinja-1.0-OpenChat-7B
---
# prueba-moe
prueba-moe is a Mixture of Experts (MoE) made with the following models using [Mergekit](https://github.com/arcee-ai/mergekit):
* [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)
## 🧩 Configuration
```yamlbase_model: mlabonne/Marcoro14-7B-slerp
experts:
- positive_prompts:
- chat
- assistant
- tell me
- explain
- what is
source_model: openchat/openchat-3.5-1210
- positive_prompts:
- code
- python
- javascript
- programming
- algorithm
source_model: beowolx/CodeNinja-1.0-OpenChat-7B
experts_per_token: 2
gate_mode: cheap_embed
```
## 💻 Usage
```python
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "mgv99/prueba-moe"
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"])
``` |