metadata
license: apache-2.0
tags:
- moe
- merge
- mergekit
model-index:
- name: Mixolar-4x7b
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: 71.08
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=shadowml/Mixolar-4x7b
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: 88.44
name: normalized accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=shadowml/Mixolar-4x7b
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: 66.29
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=shadowml/Mixolar-4x7b
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: 71.81
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=shadowml/Mixolar-4x7b
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: 83.58
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=shadowml/Mixolar-4x7b
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: 63.91
name: accuracy
source:
url: >-
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=shadowml/Mixolar-4x7b
name: Open LLM Leaderboard
Mixolar-4x7b
This model is a Mixure of Experts (MoE) made with mergekit (mixtral branch). It uses the following base models:
- kyujinpy/Sakura-SOLAR-Instruct
- jeonsworld/CarbonVillain-en-10.7B-v1
- rishiraj/meow
- kyujinpy/Sakura-SOLRCA-Math-Instruct-DPO-v2
🧩 Configuration
base_model: kyujinpy/Sakura-SOLAR-Instruct
gate_mode: hidden
experts:
- source_model: kyujinpy/Sakura-SOLAR-Instruct
positive_prompts:
- "chat"
- "assistant"
- "tell me"
- "explain"
negative_prompts:
- "mathematics"
- "reasoning"
- source_model: jeonsworld/CarbonVillain-en-10.7B-v1
positive_prompts:
- "write"
- "AI"
- "text"
- "paragraph"
negative_prompts:
- "mathematics"
- "reasoning"
- source_model: rishiraj/meow
positive_prompts:
- "chat"
- "say"
- "what"
negative_prompts:
- "mathematics"
- "reasoning"
- source_model: kyujinpy/Sakura-SOLRCA-Math-Instruct-DPO-v2
positive_prompts:
- "reason"
- "math"
- "mathematics"
- "solve"
- "count"
negative_prompts:
- "chat"
- "assistant"
- "storywriting"
💻 Usage
!pip install -qU transformers bitsandbytes accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "mlabonne/Mixolar-4x7b"
tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
"text-generation",
model=model,
model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
)
messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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. | 74.18 |
AI2 Reasoning Challenge (25-Shot) | 71.08 |
HellaSwag (10-Shot) | 88.44 |
MMLU (5-Shot) | 66.29 |
TruthfulQA (0-shot) | 71.81 |
Winogrande (5-shot) | 83.58 |
GSM8k (5-shot) | 63.91 |