LLM EXPLORER
 LLM Explorer: A Curated Large Language Model Directory and Analytics
Dark Theme
  Agents   Benchmarks   LLM  List    LLM Hosting    LLM Leaderboards    Blog    Newsfeed    Advertise

Llama 3 8B Instruct MopeyMule by failspy

 »  All LLMs  »  failspy  »  Llama 3 8B Instruct MopeyMule   URL Share it on

  25   

Llama 3 8B Instruct MopeyMule is an open-source language model by failspy. Features: 8b LLM, VRAM: 16.1GB, Context: 8K, License: other, Instruction-Based, HF Score: 57.8, LLM Explorer Score: 0.21, Arc: 56, HellaSwag: 75.6, MMLU: 59.6, TruthfulQA: 50.2, WinoGrande: 74.1, GSM8K: 31.2.

  Conversational   Deploy:azure   En   Endpoints compatible   Facebook   Instruct   Llama   Llama-3   Meta   Pytorch   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/failspy/Llama-3-8B-Instruct-MopeyMule 

Llama 3 8B Instruct MopeyMule Benchmarks

MMLU Pro: 8.49
MUSR: 2.25
BBH: 13.62
IFEval: 67.5 vs 88 (so35)-23.3%
ARC: 55.97 vs 96.7 (so35)-42.1%
HellaSwag: 75.59 vs 95.3 (gpt4)-20.7%
MMLU: 59.6 vs 88.3 (so35)-32.5%
TruthfulQA: 50.19 vs 59 (gpt4)-14.9%
WinoGrande: 74.11 vs 87.5 (gpt4)-15.3%
GSM8K: 31.24 vs 96.4 (so35)-67.6%
MATH Lvl 5: 1.96
LLME Score: 0.21064
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Llama 3 8B Instruct MopeyMule (failspy/Llama-3-8B-Instruct-MopeyMule)
🌟 Advertise your project 🚀

Llama 3 8B Instruct MopeyMule Parameters and Internals

Model Type 
text generation
Use Cases 
Areas:
commercial, research
Primary Use Cases:
assistant-like chat
Considerations:
Developers must ensure their use of the model complies with the Acceptable Use Policy and the Llama 3 Community License.
Additional Notes 
This model serves as an exploration of inducing behavioral change in LLMs via orthogonalization, generating responses with a melancholic tone. Not intended for practical applications.
Training Details 
Data Sources:
Alpaca's dataset
Methodology:
orthogonalization based on Andy Arditi et al.'s blog post technique
Context Length:
8000
Model Architecture:
auto-regressive language model with optimized transformer architecture
Input Output 
Input Format:
text only
Accepted Modalities:
text
Output Format:
text and code
Release Notes 
Version:
Llama 3 family
Date:
April 18, 2024
Notes:
Release of Llama 3 family models including instruction tuned variants optimized for dialogue use cases.
LLM NameLlama 3 8B Instruct MopeyMule
Repository 🤗https://huggingface.co/failspy/Llama-3-8B-Instruct-MopeyMule 
Model Size8b
Required VRAM16.1 GB
Updated2026-04-04
Maintainerfailspy
Model Typellama
Instruction-BasedYes
Model Files  5.0 GB: 1-of-4   5.0 GB: 2-of-4   4.9 GB: 3-of-4   1.2 GB: 4-of-4
Supported Languagesen
Model ArchitectureLlamaForCausalLM
Licenseother
Context Length8192
Model Max Length8192
Transformers Version4.40.1
Tokenizer ClassPreTrainedTokenizerFast
Vocabulary Size128256
Torch Data Typebfloat16

Best Alternatives to Llama 3 8B Instruct MopeyMule

Best Alternatives
Context / RAM
Downloads
Likes
...otron 8B UltraLong 4M Instruct4192K / 32.1 GB89119
...a 3.1 8B UltraLong 4M Instruct4192K / 32.1 GB17624
UltraLong Thinking4192K / 16.1 GB93
...a 3.1 8B UltraLong 2M Instruct2096K / 32.1 GB8759
...otron 8B UltraLong 2M Instruct2096K / 32.1 GB4017
Cthulhu 8B V1.41048K / 16.1 GB139
...otron 8B UltraLong 1M Instruct1048K / 32.1 GB344055
...a 3.1 8B UltraLong 1M Instruct1048K / 32.1 GB138729
Zero Llama 3.1 8B Beta61048K / 16.1 GB51
...dger Nu Llama 3.1 8B UltraLong1048K / 16.2 GB53
Note: green Score (e.g. "73.2") means that the model is better than failspy/Llama-3-8B-Instruct-MopeyMule.

Rank the Llama 3 8B Instruct MopeyMule Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
Censorship and Alignment  
Data Analysis and Insight Generation  
Text Generation  
Text Summarization and Feature Extraction  
Code Generation  
Multi-Language Support and Translation  

What open-source LLMs or SLMs are you in search of? 52721 in total.

Email us: info@extractum.io. Our Privacy Policy  | Terms and Conditions  | Suggest an improvement.
Our Social Media →  
Original data from HuggingFace, OpenCompass and various public git repos.
Check out Ag3ntum — our secure, self-hosted AI agent for server management.
Release v20260328a
  Support LLM Explorer