README.md

metadata

tags:
  - merge
  - mergekit
  - lazymergekit
  - paulml/DPOB-INMTOB-7B
  - bardsai/jaskier-7b-dpo-v6.1
base_model:
  - paulml/DPOB-INMTOB-7B
  - bardsai/jaskier-7b-dpo-v6.1

djinn-7b

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

• paulml/DPOB-INMTOB-7B
• bardsai/jaskier-7b-dpo-v6.1

🏆 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	±	0.0039
- humanities	N/A	none	None	acc	0.5741	±	0.0067
- other	N/A	none	None	acc	0.6933	±	0.0079
- social_sciences	N/A	none	None	acc	0.7166	±	0.0080
- stem	N/A	none	None	acc	0.5147	±	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

💻 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"])