metadata

license: apache-2.0
tags:
  - moe
  - merge
  - mergekit
  - lazymergekit
  - DopeorNope/SOLARC-M-10.7B
  - maywell/PiVoT-10.7B-Mistral-v0.2-RP
  - kyujinpy/Sakura-SOLAR-Instruct
  - jeonsworld/CarbonVillain-en-10.7B-v1

Lumosia-MoE-4x10.7

This is a very experimantal model. so have fun

Lumosia-MoE-4x10.7 is a Mixure of Experts (MoE) made with the following models:

🧩 Configuration

gate_mode: hidden
dtype: bfloat16
experts:
  - source_model: DopeorNope/SOLARC-M-10.7B
    positive_prompts: [""]
  - source_model: maywell/PiVoT-10.7B-Mistral-v0.2-RP
    positive_prompts: [""]
  - source_model: kyujinpy/Sakura-SOLAR-Instruct
    positive_prompts: [""]
  - source_model: jeonsworld/CarbonVillain-en-10.7B-v1
    positive_prompts: [""]```

## 💻 Usage

```python
!pip install -qU transformers bitsandbytes accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Steelskull/Lumosia-MoE-4x10.7"

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"])