README.md

metadata

language:
  - de
license: cc
tags:
  - merge
  - mergekit
  - lazymergekit
  - flemmingmiguel/NeuDist-Ro-7B
  - johannhartmann/Brezn3
  - ResplendentAI/Flora_DPO_7B
base_model:
  - flemmingmiguel/NeuDist-Ro-7B
  - johannhartmann/Brezn3
  - ResplendentAI/Flora_DPO_7B
model-index:
  - name: Spaetzle-v8-7b
    results:
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: AI2 Reasoning Challenge (25-Shot)
          type: ai2_arc
          config: ARC-Challenge
          split: test
          args:
            num_few_shot: 25
        metrics:
          - type: acc_norm
            value: 68.69
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cstr/Spaetzle-v8-7b
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: HellaSwag (10-Shot)
          type: hellaswag
          split: validation
          args:
            num_few_shot: 10
        metrics:
          - type: acc_norm
            value: 86.68
            name: normalized accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cstr/Spaetzle-v8-7b
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: MMLU (5-Shot)
          type: cais/mmlu
          config: all
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 64.6
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cstr/Spaetzle-v8-7b
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: TruthfulQA (0-shot)
          type: truthful_qa
          config: multiple_choice
          split: validation
          args:
            num_few_shot: 0
        metrics:
          - type: mc2
            value: 64.05
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cstr/Spaetzle-v8-7b
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: Winogrande (5-shot)
          type: winogrande
          config: winogrande_xl
          split: validation
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 81.45
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cstr/Spaetzle-v8-7b
          name: Open LLM Leaderboard
      - task:
          type: text-generation
          name: Text Generation
        dataset:
          name: GSM8k (5-shot)
          type: gsm8k
          config: main
          split: test
          args:
            num_few_shot: 5
        metrics:
          - type: acc
            value: 68.16
            name: accuracy
        source:
          url: >-
            https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=cstr/Spaetzle-v8-7b
          name: Open LLM Leaderboard

Spaetzle-v8-7b

Spaetzle-v8-7b is a merge of the following models using LazyMergekit:

• flemmingmiguel/NeuDist-Ro-7B
• johannhartmann/Brezn3
• ResplendentAI/Flora_DPO_7B

🧩 Configuration

models:
  - model: mayflowergmbh/Wiedervereinigung-7b-dpo-laser
    # no parameters necessary for base model
  - model: flemmingmiguel/NeuDist-Ro-7B
    parameters:
      density: 0.60
      weight: 0.30
  - model: johannhartmann/Brezn3
    parameters:
      density: 0.65
      weight: 0.40
  - model: ResplendentAI/Flora_DPO_7B
    parameters:
      density: 0.6
      weight: 0.3
merge_method: dare_ties
base_model: mayflowergmbh/Wiedervereinigung-7b-dpo-laser
parameters:
  int8_mask: true
dtype: bfloat16
random_seed: 0
tokenizer_source: base

💻 Usage

!pip install -qU transformers accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "cstr/Spaetzle-v8-7b"
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.	72.27
AI2 Reasoning Challenge (25-Shot)	68.69
HellaSwag (10-Shot)	86.68
MMLU (5-Shot)	64.60
TruthfulQA (0-shot)	64.05
Winogrande (5-shot)	81.45
GSM8k (5-shot)	68.16