README.md

metadata

tags:
  - merge
  - mergekit
  - lazymergekit
  - DreadPoor/Eunoia_Vespera-8B-LINEAR
  - DreadPoor/Promissum_Mane-8B-LINEAR-lorablated
base_model:
  - DreadPoor/Eunoia_Vespera-8B-LINEAR
  - DreadPoor/Promissum_Mane-8B-LINEAR-lorablated
model-index:
  - name: DreadMix
    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: 70.95
            name: strict accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=BoltMonkey/DreadMix
          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: 34.85
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=BoltMonkey/DreadMix
          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: 13.75
            name: exact match
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=BoltMonkey/DreadMix
          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: 6.6
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=BoltMonkey/DreadMix
          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: 13.62
            name: acc_norm
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=BoltMonkey/DreadMix
          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: 31
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=BoltMonkey/DreadMix
          name: Open LLM Leaderboard

DreadMix

DreadMix is a merge of the following models using LazyMergekit:

• DreadPoor/Eunoia_Vespera-8B-LINEAR
• DreadPoor/Promissum_Mane-8B-LINEAR-lorablated

🧩 Configuration

models:
  - model: DreadPoor/Aurora_faustus-8B-LORABLATED_ALT
  - model: DreadPoor/Eunoia_Vespera-8B-LINEAR
    parameters:
      density: 0.53
      weight: 0.55
  - model: DreadPoor/Promissum_Mane-8B-LINEAR-lorablated
    parameters:
      density: 0.53
      weight: 0.45
merge_method: dare_ties
base_model: DreadPoor/Aurora_faustus-8B-LORABLATED_ALT
parameters:
  int8_mask: true
dtype: bfloat16

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "BoltMonkey/DreadMix"
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.	28.46
IFEval (0-Shot)	70.95
BBH (3-Shot)	34.85
MATH Lvl 5 (4-Shot)	13.75
GPQA (0-shot)	6.60
MuSR (0-shot)	13.62
MMLU-PRO (5-shot)	31.00