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Adding Evaluation Results (#1)
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metadata
tags:
  - merge
  - mergekit
  - lazymergekit
  - arcee-ai/Llama-3.1-SuperNova-Lite
base_model:
  - arcee-ai/Llama-3.1-SuperNova-Lite
model-index:
  - name: 1PARAMMYL-8B-ModelStock
    results:
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: IFEval (0-Shot)
          type: HuggingFaceH4/ifeval
          args:
            num_few_shot: 0
        metrics:
          - type: inst_level_strict_acc and prompt_level_strict_acc
            value: 53.71
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Youlln/1PARAMMYL-8B-ModelStock
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: BBH (3-Shot)
          type: BBH
          args:
            num_few_shot: 3
        metrics:
          - type: acc_norm
            value: 31.8
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Youlln/1PARAMMYL-8B-ModelStock
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MATH Lvl 5 (4-Shot)
          type: hendrycks/competition_math
          args:
            num_few_shot: 4
        metrics:
          - type: exact_match
            value: 13.14
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Youlln/1PARAMMYL-8B-ModelStock
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: GPQA (0-shot)
          type: Idavidrein/gpqa
          args:
            num_few_shot: 0
        metrics:
          - type: acc_norm
            value: 9.84
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Youlln/1PARAMMYL-8B-ModelStock
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MuSR (0-shot)
          type: TAUR-Lab/MuSR
          args:
            num_few_shot: 0
        metrics:
          - type: acc_norm
            value: 14.28
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Youlln/1PARAMMYL-8B-ModelStock
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MMLU-PRO (5-shot)
          type: TIGER-Lab/MMLU-Pro
          config: main
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 33.34
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=Youlln/1PARAMMYL-8B-ModelStock
          name: Open LLM Leaderboard

1PARAMMYL-8B-ModelStock

1PARAMMYL-8B-ModelStock is a merge of the following models using LazyMergekit:

🧩 Configuration

slices:
  - sources:
      - model: arcee-ai/Llama-3.1-SuperNova-Lite
        layer_range: [0, 32]
      - model: DreadPoor/Heart_Stolen-8B-Model_Stock
        layer_range: [0, 32]
      - model: Dampfinchen/Llama-3.1-8B-Ultra-Instruct
        layer_range: [0, 32]
merge_method: model_stock
base_model: arcee-ai/Llama-3.1-SuperNova-Lite
dtype: bfloat16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "Youlln/1PARAMMYL-8B-ModelStock"
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. 26.02
IFEval (0-Shot) 53.71
BBH (3-Shot) 31.80
MATH Lvl 5 (4-Shot) 13.14
GPQA (0-shot) 9.84
MuSR (0-shot) 14.28
MMLU-PRO (5-shot) 33.34