Hugo-7B-slerp

Hugo-7B-slerp

<p align="center"> <img src="https://cdn.openart.ai/stable_diffusion/54be6f0516fee5ce9b3f8a8b68620a05059fc4cf_2000x2000.webp" alt="alt text" class="center" width="300"/> </p>

Hugo-7B-slerp is a successful merge of the following models using mergekit:

• mistralai/Mistral-7B-Instruct-v0.2
• beowolx/CodeNinja-1.0-OpenChat-7B

🧩 Configuration

slices:
  - sources:
      - model: mistralai/Mistral-7B-Instruct-v0.2
        layer_range: [0, 32]
      - model: beowolx/CodeNinja-1.0-OpenChat-7B
        layer_range: [0, 32]
merge_method: slerp
base_model: mistralai/Mistral-7B-Instruct-v0.2
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

📈 Performance

With bold one can see the benchmarks where this merge overtakes the basemodel in performance.

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

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

tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
    "conversational",
    model=model,
    torch_dtype=torch.float16,
    device_map="auto",
)

outputs = pipeline(messages, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
print(outputs)

🛈 More on megekit

mergekit

Open LLM Leaderboard Evaluation Results

Detailed results can be found here