If you're interested in my models, you can vote for them to be evaluated on the Leadarboard.

GutenLaserPi

GutenLaserPi is a merge of the following models using LazyMergekit:

🧩 Configuration

slices:
  - sources:
      - model: flammenai/flammen15-gutenberg-DPO-v1-7B
        layer_range: [0, 32]
      - model: Eric111/CatunaLaserPi
        layer_range: [0, 32]
merge_method: slerp
base_model: Eric111/CatunaLaserPi
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

πŸ’» Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Stark2008/GutenLaserPi"
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. 21.29
IFEval (0-Shot) 42.27
BBH (3-Shot) 32.98
MATH Lvl 5 (4-Shot) 7.18
GPQA (0-shot) 4.92
MuSR (0-shot) 16.99
MMLU-PRO (5-shot) 23.40
Downloads last month
33
Safetensors
Model size
7.24B params
Tensor type
BF16
Β·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for Stark2008/GutenLaserPi

Merge model
this model
Finetunes
1 model
Quantizations
2 models

Evaluation results