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VisFlamCat

VisFlamCat is a merge of the following models using LazyMergekit:

🧩 Configuration

models:
  - model: Nitral-AI/Visual-LaylelemonMaidRP-7B
    #no parameters necessary for base model
  - model: flammenai/flammen15-gutenberg-DPO-v1-7B
    parameters:
      density: 0.5
      weight: 0.5
  - model: Eric111/CatunaLaserPi
    parameters:
      density: 0.5
      weight: 0.5

merge_method: ties
base_model: Nitral-AI/Visual-LaylelemonMaidRP-7B
parameters:
  normalize: false
  int8_mask: true
dtype: float16

πŸ’» Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Stark2008/VisFlamCat"
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. 21.16
IFEval (0-Shot) 43.66
BBH (3-Shot) 32.88
MATH Lvl 5 (4-Shot) 6.57
GPQA (0-shot) 5.37
MuSR (0-shot) 14.68
MMLU-PRO (5-shot) 23.82
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Model size
7.24B params
Tensor type
FP16
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Evaluation results