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Ministral-8B-slerp

Ministral-8B-slerp is a merge of the following models using LazyMergekit:

🧩 Configuration

slices:
  - sources:
      - model: prince-canuma/Ministral-8B-Instruct-2410-HF
        layer_range: [0, 32]
      - model: prince-canuma/Ministral-8B-Instruct-2410-HF
        layer_range: [0, 32]
merge_method: slerp
base_model: prince-canuma/Ministral-8B-Instruct-2410-HF
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: float32

πŸ’» Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "allknowingroger/Ministral-8B-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"])

Open LLM Leaderboard Evaluation Results

Detailed results can be found here

Metric Value
Avg. 14.84
IFEval (0-Shot) 19.61
BBH (3-Shot) 25.20
MATH Lvl 5 (4-Shot) 0.00
GPQA (0-shot) 8.28
MuSR (0-shot) 12.40
MMLU-PRO (5-shot) 23.55
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Model size
7.25B params
Tensor type
F32
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Evaluation results