metadata
license: apache-2.0
tags:
- merge
- mergekit
- lazymergekit
- zhengr/MixTAO-7Bx2-MoE-v8.1
- RubielLabarta/LogoS-7Bx2-MoE-13B-v0.2
base_model:
- zhengr/MixTAO-7Bx2-MoE-v8.1
- RubielLabarta/LogoS-7Bx2-MoE-13B-v0.2
model-index:
- name: MultiMash10-13B-slerp
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: 41.63
name: strict accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allknowingroger/MultiMash10-13B-slerp
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: 32.45
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allknowingroger/MultiMash10-13B-slerp
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: 6.34
name: exact match
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allknowingroger/MultiMash10-13B-slerp
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: 4.81
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allknowingroger/MultiMash10-13B-slerp
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: 12.97
name: acc_norm
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allknowingroger/MultiMash10-13B-slerp
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: 23.52
name: accuracy
source:
url: >-
https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=allknowingroger/MultiMash10-13B-slerp
name: Open LLM Leaderboard
MultiMash10-13B-slerp
MultiMash10-13B-slerp is a merge of the following models using LazyMergekit:
🧩 Configuration
slices:
- sources:
- model: zhengr/MixTAO-7Bx2-MoE-v8.1
layer_range: [0, 32]
- model: RubielLabarta/LogoS-7Bx2-MoE-13B-v0.2
layer_range: [0, 32]
merge_method: slerp
base_model: zhengr/MixTAO-7Bx2-MoE-v8.1
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 = "allknowingroger/MultiMash10-13B-slerp"
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. | 20.29 |
IFEval (0-Shot) | 41.63 |
BBH (3-Shot) | 32.45 |
MATH Lvl 5 (4-Shot) | 6.34 |
GPQA (0-shot) | 4.81 |
MuSR (0-shot) | 12.97 |
MMLU-PRO (5-shot) | 23.52 |