README.md

metadata

license: apache-2.0
tags:
  - moe
  - frankenmoe
  - merge
  - mergekit
  - lazymergekit
  - Gille/StrangeMerges_9-7B-dare_ties
  - Gille/StrangeMerges_8-7B-slerp
base_model:
  - Gille/StrangeMerges_9-7B-dare_ties
  - Gille/StrangeMerges_8-7B-slerp

MoE-StrangeMerges-2x7B

MoE-StrangeMerges-2x7B is a Mixure of Experts (MoE) made with the following models using LazyMergekit:

• Gille/StrangeMerges_9-7B-dare_ties
• Gille/StrangeMerges_8-7B-slerp

🧩 Configuration

base_model: Gille/StrangeMerges_9-7B-dare_ties
gate_mode: cheap_embed
dtype: float16
experts:
  - source_model: Gille/StrangeMerges_9-7B-dare_ties
    positive_prompts: ["science, logic, math"]
  - source_model: Gille/StrangeMerges_8-7B-slerp
    positive_prompts: ["reasoning, numbers, abstract"]

💻 Usage

!pip install -qU transformers bitsandbytes accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Gille/MoE-StrangeMerges-2x7B"

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"])