djinn-7b
djinn-7b is a merge of the following models using LazyMergekit:
🏆 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"])