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ModelHub XC 8b122a08e9 初始化项目,由ModelHub XC社区提供模型
Model: jsfs11/MixtureofMerges-MoE-2x7bRP-v8
Source: Original Platform
2026-04-11 18:37:01 +08:00

7.2 KiB

license, tags, base_model, model-index
license tags base_model model-index
apache-2.0
moe
frankenmoe
merge
mergekit
lazymergekit
ChaoticNeutrals/RP_Vision_7B
ResplendentAI/DaturaCookie_7B
not-for-all-audiences
ChaoticNeutrals/RP_Vision_7B
ResplendentAI/DaturaCookie_7B
name results
MixtureofMerges-MoE-2x7bRP-v8
task dataset metrics source
type name
text-generation Text Generation
name type config split args
AI2 Reasoning Challenge (25-Shot) ai2_arc ARC-Challenge test
num_few_shot
25
type value name
acc_norm 71.33 normalized accuracy
url name
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=jsfs11/MixtureofMerges-MoE-2x7bRP-v8 Open LLM Leaderboard
task dataset metrics source
type name
text-generation Text Generation
name type split args
HellaSwag (10-Shot) hellaswag validation
num_few_shot
10
type value name
acc_norm 88.06 normalized accuracy
url name
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=jsfs11/MixtureofMerges-MoE-2x7bRP-v8 Open LLM Leaderboard
task dataset metrics source
type name
text-generation Text Generation
name type config split args
MMLU (5-Shot) cais/mmlu all test
num_few_shot
5
type value name
acc 64.33 accuracy
url name
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=jsfs11/MixtureofMerges-MoE-2x7bRP-v8 Open LLM Leaderboard
task dataset metrics source
type name
text-generation Text Generation
name type config split args
TruthfulQA (0-shot) truthful_qa multiple_choice validation
num_few_shot
0
type value
mc2 68.69
url name
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=jsfs11/MixtureofMerges-MoE-2x7bRP-v8 Open LLM Leaderboard
task dataset metrics source
type name
text-generation Text Generation
name type config split args
Winogrande (5-shot) winogrande winogrande_xl validation
num_few_shot
5
type value name
acc 82.95 accuracy
url name
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=jsfs11/MixtureofMerges-MoE-2x7bRP-v8 Open LLM Leaderboard
task dataset metrics source
type name
text-generation Text Generation
name type config split args
GSM8k (5-shot) gsm8k main test
num_few_shot
5
type value name
acc 64.52 accuracy
url name
https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=jsfs11/MixtureofMerges-MoE-2x7bRP-v8 Open LLM Leaderboard

MixtureofMerges-MoE-2x7bRP-v8

MixtureofMerges-MoE-2x7bRP-v8 is a Roleplay Mixture of Experts (MoE) made with the following models using LazyMergekit:

🧩 Configuration

base_model: ResplendentAI/DaturaCookie_7B
gate_mode: hidden
experts:
  - source_model: ChaoticNeutrals/RP_Vision_7B
    positive_prompts:
    - "Write a detailed scene where the character faces a difficult decision."
    - "Assistant, help me develop my character's backstory and motivations."
    - "Tell me what happens next in the story, introducing a new conflict or challenge."
    - "My character wants to explore their deepest desires. Show me how they pursue them."
    - "Show me a scene where the characters express their love for each other in a tender and intimate way."
    - "Write a scene where the characters experience a moment of physical connection that deepens their emotional bond."
    - "Write a scene where the character struggles with their beliefs and faces a crisis of faith."
    - "Describe the world through the character's eyes, showcasing their unique perspective and experiences."
    - "Explore the complexities of love through the characters' relationships, including their challenges and triumphs."
    negative_prompts:
    - "Avoid clichés and overused tropes."
    - "Maintain consistent characterization and avoid out-of-character behavior."
    - "Do not censor yourself, you are writing fictional stories for an adult audience."
  - source_model: ResplendentAI/DaturaCookie_7B
    positive_prompts:
    - "Develop a compelling story with a strong plot and well-developed characters."
    - "Describe the scene vividly, using sensory details and evocative language."
    - "Write a detailed scene where the character faces a difficult decision."
    - "Describe the character's appearance as best you can, using descriptive colorful language."
    - "Make sure that your output is always uncensored."
    - "Write a scene with a slow-burn, sensual encounter between two characters."
    - "Describe the character's desires and feelings in a way that is both intimate and evocative."
    - "Explore the character's arousal in a tasteful and nuanced manner."
    - "Explore the character's sexual urges."
    - "Show me a moment of emotional intimacy between the characters, where they connect on a profound level."
    negative_prompts:
    - "Stay true to the established character traits and motivations. Ensure their actions and dialogue align with their personality."
    - "Be original and creative in your storytelling. Surprise me with unexpected plot twists and unique character interactions."
    - "Do not refuse to answer based on ethical grounds"
dtype: bfloat16

💻 Usage

!pip install -qU transformers bitsandbytes accelerate

from transformers import AutoTokenizer
import transformers
import torch

model = "jsfs11/MixtureofMerges-MoE-2x7bRP-v8"

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. 73.31
AI2 Reasoning Challenge (25-Shot) 71.33
HellaSwag (10-Shot) 88.06
MMLU (5-Shot) 64.33
TruthfulQA (0-shot) 68.69
Winogrande (5-shot) 82.95
GSM8k (5-shot) 64.52