MoE Lumina Models
Collection
A collection of different Lumina MoE models. • 6 items • Updated
Lumina-RP
Lumina-4 is a Mixture of Experts (MoE) made with LazyMergekit. This model has improved roleplaying and storytelling from Lumina-3.5 while still retaining its strength. A slight improvement on the Open LLM leaderboard. It uses a context window of up to 32k.
Response Examples
Input: 25 - 4 * 2 + 3 = ?
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Output: The given mathematical expression is 25 - 4 * 2 + 3. To solve it, we should follow the order of operations (PEMDAS):
1. Parentheses: There are none in this equation.
2. Exponents: None present.
3. Multiplication and Division: We perform multiplications before divisions from left to right. In this case, 4 * 2 = 8. Now our equation becomes 25 - 8 + 3.
4. Addition and Subtraction: We perform additions before subtractions from left to right. Here, we have a subtraction then an addition: 25 - 8 = 17, then 17 + 3 = 20.
So the result of the expression 25 - 4 * 2 + 3 is 20.
🏆 Open LLM Leaderboard Evaluation Results
| Metric | Value |
|---|---|
| Avg. | 75.59 |
| AI2 Reasoning Challenge (25-Shot) | 72.61 |
| HellaSwag (10-Shot) | 88.45 |
| MMLU (5-Shot) | 64.73 |
| TruthfulQA (0-shot) | 74.24 |
| Winogrande (5-shot) | 83.90 |
| GSM8k (5-shot) | 69.60 |
💻 Usage
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "Ppoyaa/Lumina-4"
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"])
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