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Spring Chicken 8x8b by maldv

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  Conversational   Endpoints compatible   Llama-3   Mixtral   Moe   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/maldv/spring-chicken-8x8b 

Spring Chicken 8x8b Benchmarks

ARC: 63.05 vs 96.7 (so35)-34.8%
HellaSwag: 82.49 vs 95.3 (gpt4)-13.4%
MMLU: 64.45 vs 88.3 (so35)-27%
TruthfulQA: 51.63 vs 59 (gpt4)-12.5%
WinoGrande: 76.24 vs 87.5 (gpt4)-12.9%
GSM8K: 57.47 vs 96.4 (so35)-40.4%
LLME Score: 0.15601
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Spring Chicken 8x8b (maldv/spring-chicken-8x8b)
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Spring Chicken 8x8b Parameters and Internals

Model Type 
emotive RP model
Use Cases 
Areas:
emotive role-playing
Additional Notes 
Llama 3 instruct format works well; minimal format is highly creative.
Training Details 
Methodology:
Cascading dare-ties merge
LLM NameSpring Chicken 8x8b
Repository 🤗https://huggingface.co/maldv/spring-chicken-8x8b 
Model Size47.5b
Required VRAM95.1 GB
Updated2026-02-25
Maintainermaldv
Model Typemixtral
Model Files  10.0 GB: 1-of-10   10.0 GB: 2-of-10   10.0 GB: 3-of-10   10.0 GB: 4-of-10   10.0 GB: 5-of-10   10.0 GB: 6-of-10   10.0 GB: 7-of-10   10.0 GB: 8-of-10   10.0 GB: 9-of-10   5.1 GB: 10-of-10
Model ArchitectureMixtralForCausalLM
Licensecc-by-nc-4.0
Context Length8192
Model Max Length8192
Transformers Version4.40.1
Tokenizer ClassPreTrainedTokenizerFast
Padding Token<|begin_of_text|>
Vocabulary Size128256
Torch Data Typebfloat16

Best Alternatives to Spring Chicken 8x8b

Best Alternatives
Context / RAM
Downloads
Likes
...k Planet 8D Mirrored Chaos 47B8K / 94.9 GB1273
Llama 3 8B Instruct MoE 48K / 95.2 GB50
Mixllama3 8x8b Instruct V0.18K / 95.3 GB04
... Mirrored Chaos Uncensored 47B128K / 94.9 GB2021
Note: green Score (e.g. "73.2") means that the model is better than maldv/spring-chicken-8x8b.

Rank the Spring Chicken 8x8b 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  

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