🧠 ZeroXClem-Llama-3.1-8B-Athena-Apollo-exp
Overview
ZeroXClem-Llama-3.1-8B-Athena-Apollo-exp is a powerful AI model built through Model Stock merging using MergeKit. It merges several of the most capable and nuanced Llama-3.1-based models available on Hugging Face, optimized for performance across instruction-following, roleplay, logic, coding, and creative writing tasks.
By fusing diverse fine-tuned architectures into a cohesive blended model, this creation delivers excellent generalist abilities while retaining specialized strengths.
🔧 Merge Details
- Merge Method:
model_stock
- Base Model:
mergekit-community/L3.1-Athena-l3-8B
- Dtype:
bfloat16
- Tokenizer Source:
mergekit-community/L3.1-Athena-l3-8B
💡 Models Merged
The following models contribute to this powerful fusion:
rootxhacker/Apollo-exp-8B
— A rich blend focused on alignment, DPO, and SFT instruction tuning across Llama-3.1 variants.mergekit-community/L3.1-Athena-k-8B
— Roleplay and safety-aligned merge based on Meta's Llama-3.1 foundation.mergekit-community/L3.1-Athena-l2-8B
— LoRA-enhanced with long-context and creative capability merges.mergekit-community/L3.1-Athena-l-8B
— Deeply infused with LoRA-based domain-specific models in logic, psychology, storytelling, and more.
🧪 Configuration
name: ZeroXClem-Llama-3.1-8B-Athena-Apollo-exp
base_model: mergekit-community/L3.1-Athena-l3-8B
dtype: bfloat16
merge_method: model_stock
models:
- model: rootxhacker/Apollo-exp-8B
- model: mergekit-community/L3.1-Athena-k-8B
- model: mergekit-community/L3.1-Athena-l2-8B
- model: mergekit-community/L3.1-Athena-l-8B
tokenizer_source: mergekit-community/L3.1-Athena-l3-8B
✨ Features & Highlights
🔹 Instruction-Following Prowess — Merged from Tulu-aligned and instruct-tuned models like Apollo-exp and Athena-k for high-quality, context-aware responses.
🔹 Immersive Roleplay & Personality — Strong roleplay personas and emotional nuance thanks to Athena's diverse RP blends.
🔹 Creative & Structured Generation — Support for creative writing, long-context novelization, and formal logic modeling from l2/l3 integrations.
🔹 Depth in Dialogue — Enhanced ability to carry layered and philosophical conversation from Claude-style fine-tunes in Apollo-exp.
🎯 Use Cases
- Conversational AI & Roleplay Bots
- Formal Reasoning & Chain-of-Thought Tasks
- Creative Writing & Storytelling Tools
- Coding Assistants
- Educational and Research Applications
🛠️ Usage Instructions
from transformers import AutoModelForCausalLM, AutoTokenizer
model_name = "ZeroXClem/Llama-3.1-8B-Athena-Apollo-exp"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype="auto", device_map="auto")
prompt = "Explain quantum entanglement like I'm 10 years old."
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
outputs = model.generate(**inputs, max_new_tokens=200)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
🦙 Ollama Instructions
ollama run hf.co/ZeroXClem/Llama-3.1-8B-Athena-Apollo-exp-Q4_K_M-GGUF
🧭 Alignment & Ethics
⚠️ Unfiltered Output: This model is uncensored and may generate content outside of alignment norms. Please implement your own moderation layers when deploying in production environments.
⚠️ Responsible Use: Developers are encouraged to audit outputs and maintain ethical usage policies for downstream applications.
📜 License: Usage governed by the Meta Llama 3.1 Community License.
💌 Feedback & Contributions
We welcome your feedback, benchmarks, and improvements! Please open an issue or PR to contribute or tag us in your results and projects.
ZeroXClem Team | 2025
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