MonarchPipe-7B-slerp

<img src="https://cdn-uploads.huggingface.co/production/uploads/6389d3c61e8755d777902366/7dTpG4vJWkB4YwBJFCqoE.jpeg" style="border-radius:2%; width: 66%">

MonarchPipe-7B-slerp

MonarchPipe-7B-slerp is a merge of the following models using LazyMergekit:

• OpenPipe/mistral-ft-optimized-1227
• mlabonne/AlphaMonarch-7B

🏆 Eval

Nous

Eval results from the Nous benchmark suite (performed using LLM AutoEval).

🧩 Configuration

slices:
  - sources:
      - model: OpenPipe/mistral-ft-optimized-1227
        layer_range: [0, 32]
      - model: mlabonne/AlphaMonarch-7B
        layer_range: [0, 32]
merge_method: slerp
base_model: OpenPipe/mistral-ft-optimized-1227
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
dtype: bfloat16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "ichigoberry/MonarchPipe-7B-slerp"
messages = [{"role": "user", "content": "What is a large language model?"}]

tokenizer = AutoTokenizer.from_pretrained(model)
prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
pipeline = transformers.pipeline(
    "text-generation",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

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"])