djinn-7b

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

πŸ† Benchmarks

Open LLM Leaderboard

Model Average ARC_easy HellaSwag MMLU TruthfulQA_mc2 Winogrande GSM8K
mayacinka/djinn-7B 78.40 86.7 87.37 61.84 77.23 82.64 74.68

MMLU (per category)

Groups Version Filter n-shot Metric Value Stderr
mmlu N/A none 0 acc 0.6184 Β± 0.0039
- humanities N/A none None acc 0.5741 Β± 0.0067
- other N/A none None acc 0.6933 Β± 0.0079
- social_sciences N/A none None acc 0.7166 Β± 0.0080
- stem N/A none None acc 0.5147 Β± 0.0085

AutoEval

Maxime Labonne's autoeval notebook

Model AGIEval GPT4All TruthfulQA Bigbench Average
djinn-7b 44.9 77.33 77.18 49.36 62.19

🧩 Configuration

slices:
  - sources:
      - model: paulml/DPOB-INMTOB-7B
        layer_range: [0, 32]
      - model: bardsai/jaskier-7b-dpo-v6.1
        layer_range: [0, 32]
merge_method: slerp
base_model: paulml/DPOB-INMTOB-7B
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 = "mayacinka/djinn-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"])
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