L3.1 8B Celeste V1.5 by nothingiisreal

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  Autotrain compatible   Conversational Dataset:kalomaze/opus instruct... Dataset:nothingiisreal/c2-logs... Dataset:nothingiisreal/reddit-...   En   Endpoints compatible   Instruct   Llama   Not-for-all-audiences   Region:us   Safetensors   Sharded   Tensorflow

L3.1 8B Celeste V1.5 Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
L3.1 8B Celeste V1.5 (nothingiisreal/L3.1-8B-Celeste-V1.5)
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L3.1 8B Celeste V1.5 Parameters and Internals

Model Type 
text generation, roleplaying, instruction following
Use Cases 
Areas:
Roleplaying, Creative Writing
Applications:
Text-based storytelling, Character-driven narratives
Primary Use Cases:
Roleplay context following, Creative story generation
Limitations:
High complexity narrative structures might falter, Not always SFW without explicit control prompts
Considerations:
Engage with tailored system messages and OOC instructions for optimal behavior
Additional Notes 
Focused on enhancing narrative coherence and minimizing non-responsive behavior.
Supported Languages 
English (fluent), Others (unknown)
Training Details 
Data Sources:
Reddit Writing Prompts, Kalo's Opus 25K Instruct, C2 logs cleaned, Dirty Writing Prompts
Data Volume:
8K context sequences
Methodology:
Fine-tuning with diverse datasets & instruction following
Context Length:
8192
Training Time:
1 hour using 1xH100 SXM
Hardware Used:
1x H100 SXM GPU
Model Architecture:
Fine-tuned variant of LLaMA 3.1 with additional roleplay and instruct objectives
Safety Evaluation 
Methodologies:
OOC steering, system messaging
Findings:
Adheres to specific steering prompts, Variable response behavior under different contexts
Risk Categories:
Influence, NSFW content potential
Ethical Considerations:
The model can drift content into NSFW without user intent if prompted incorrectly
Responsible Ai Considerations 
Fairness:
Trained on diverse sources for varied perspectives
Transparency:
Open about training datasets and methodology
Accountability:
User's responsibility for misuse
Mitigation Strategies:
Uses OOC prompts and prefill for harmful topic management
Input Output 
Input Format:
Structured roleplay prompts
Accepted Modalities:
text
Output Format:
Text-based responses
Performance Tips:
Use OOC prompts for role consistency; refine initial and follow-up prompts for desired context
Release Notes 
Version:
V1.5
Date:
Unknown
Notes:
Improved creativity and fewer instruction refusals, enhanced training ratio management
LLM NameL3.1 8B Celeste V1.5
Repository ๐Ÿค—https://huggingface.co/nothingiisreal/L3.1-8B-Celeste-V1.5 
Model Size8b
Required VRAM16.1 GB
Updated2025-09-07
Maintainernothingiisreal
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
Licensellama3.1
Context Length131072
Model Max Length131072
Transformers Version4.43.1
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|end_of_text|>
Vocabulary Size128256
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than nothingiisreal/L3.1-8B-Celeste-V1.5.

Rank the L3.1 8B Celeste V1.5 Capabilities

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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  

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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124