language:
- en
license: apache-2.0
library_name: transformers
tags:
- merge
- mergekit
- lazymergekit
- model_stock
- ZeroXClem-Llama-3.1-8B-AthenaSky-MegaMix
base_model:
- Pedro13543/mega_blend_model
- Skywork/Skywork-o1-Open-Llama-3.1-8B
- Undi95/Meta-Llama-3.1-8B-Claude
- mergekit-community/good_mix_model_Stock
- mergekit-community/L3.1-Athena-d-8B
pipeline_tag: text-generation
model-index:
- name: Llama-3.1-8B-AthenaSky-MegaMix
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: 63.01
name: strict accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ZeroXClem/Llama-3.1-8B-AthenaSky-MegaMix
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: 31.39
name: normalized accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ZeroXClem/Llama-3.1-8B-AthenaSky-MegaMix
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: 27.95
name: exact match
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ZeroXClem/Llama-3.1-8B-AthenaSky-MegaMix
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: 3.69
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ZeroXClem/Llama-3.1-8B-AthenaSky-MegaMix
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: 6.9
name: acc_norm
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ZeroXClem/Llama-3.1-8B-AthenaSky-MegaMix
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: 27.82
name: accuracy
source:
url: https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query=ZeroXClem/Llama-3.1-8B-AthenaSky-MegaMix
name: Open LLM Leaderboard
ZeroXClem-Llama-3.1-8B-AthenaSky-MegaMix
Overview
ZeroXClem-Llama-3.1-8B-AthenaSky-MegaMix is a powerful AI model built through model stock merging using MergeKit. It brings together some of the best models available on Hugging Face, ensuring strong performance in a wide range of NLP tasks, including reasoning, coding, roleplay, and instruction-following.

This model was created by merging high-quality foundational and fine-tuned models to create an optimized blended architecture that retains the strengths of each contributing model.
Merge Details
Models Merged
The following models contributed to this fusion:
Configuration
name: ZeroXClem-Llama-3.1-8B-AthenaSky-MegaMix
base_model: mergekit-community/L3.1-Athena-d-8B
dtype: bfloat16
merge_method: model_stock
models:
- model: Pedro13543/mega_blend_model
- model: Skywork/Skywork-o1-Open-Llama-3.1-8B
- model: Undi95/Meta-Llama-3.1-8B-Claude
- model: mergekit-community/good_mix_model_Stock
tokenizer_source: mergekit-community/L3.1-Athena-d-8B
Features & Improvements
š¹ Advanced Reasoning & Thoughtfulness - Thanks to Skywork-o1
integration, this model excels in logical thinking and problem-solving.
š¹ Enhanced Conversational Depth - The inclusion of Meta-Llama-3.1-8B-Claude
adds better response structuring, making it more engaging in dialogue.
š¹ Versatile Roleplay & Creativity - Leveraging mega_blend_model
and good_mix_model_Stock
, the model supports immersive roleplaying and storytelling.
š¹ Strong Instruction Following - Trained on various instruction datasets to provide clear, informative, and helpful responses.
Use Cases
- Chat & Roleplay - Supports natural, engaging, and dynamic conversational flow.
- Programming & Code Generation - Provides reliable code completions and debugging suggestions.
- Creative Writing - Generates compelling stories, character dialogues, and immersive text.
- Educational Assistance - Helps explain complex topics and answer academic questions.
- Logic & Problem-Solving - Can handle reasoning-based and structured thought processes.
š How to Use
š„ Ollama (Quick Inference)
You can run the model using Ollama for direct testing:
ollama run hf.co/ZeroXClem/Llama-3.1-8B-AthenaSky-MegaMix
š¤ Hugging Face Transformers (Python)
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
import torch
model_name = "ZeroXClem/Llama-3.1-8B-AthenaSky-MegaMix"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(
model_name,
torch_dtype=torch.bfloat16,
device_map="auto"
)
text_generator = pipeline(
"text-generation",
model=model,
tokenizer=tokenizer,
torch_dtype=torch.bfloat16,
device_map="auto"
)
prompt = "Describe the significance of AI ethics in modern technology."
outputs = text_generator(
prompt,
max_new_tokens=200,
do_sample=True,
temperature=0.7,
top_k=50,
top_p=0.95
)
print(outputs[0]["generated_text"])
Model Alignment & Ethics
ā ļø Uncensored Use: This model does not apply strict moderation. Users should implement appropriate safety filters before deployment.
ā ļø Responsibility Notice: You are responsible for the outputs generated by this model. It is recommended to apply ethical safeguards and content moderation when integrating this model into applications.
š License: Governed by the Meta Llama 3.1 Community License Agreement.
Feedback & Contributions
We welcome feedback, bug reports, and performance evaluations! If you find improvements or wish to contribute, feel free to reach out or submit suggestions.
**ZeroXClem Team | 2025 ** 
Detailed results can be found here
Metric |
Value |
Avg. |
26.79 |
IFEval (0-Shot) |
63.01 |
BBH (3-Shot) |
31.39 |
MATH Lvl 5 (4-Shot) |
27.95 |
GPQA (0-shot) |
3.69 |
MuSR (0-shot) |
6.90 |
MMLU-PRO (5-shot) |
27.82 |