Minerva-MoE-3x3B
Minerva-MoE-3x3B is a Mixture of Experts (MoE) made with the following models using LazyMergekit:
Evaluation
arc_it acc_norm: 31.91 hellaswag_it acc_norm: 52.20 mmmlu_it: 25.72
🧩 Configuration
base_model: sapienzanlp/Minerva-3B-base-v1.0
experts:
- source_model: DeepMount00/Minerva-3B-base-RAG
positive_prompts:
- "rispondi a domande"
- "cosa è"
- "chi è"
- "dove è"
- "come si"
- "spiegami"
- "definisci"
- source_model: FairMind/Minerva-3B-Instruct-v1.0
positive_prompts:
- "istruzione"
- "input"
- "risposta"
- "scrivi"
- "sequenza"
- "istruzioni"
dtype: bfloat16
💻 Usage
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "ludocomito/Minerva-MoE-3x3B"
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"])