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TinyllamaMix 1.1B by Aryanne

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TinyllamaMix 1.1B is an open-source language model by Aryanne. Features: 1.1b LLM, VRAM: 2.2GB, Context: 32K, License: apache-2.0, Quantized, HF Score: 33, LLM Explorer Score: 0.16, Arc: 31.5, HellaSwag: 48.4, MMLU: 25.1, TruthfulQA: 33.5, WinoGrande: 58.5, GSM8K: 1.1.

  Endpoints compatible   Gguf   Llama   Model-index   Q8   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/Aryanne/TinyllamaMix-1.1B 

TinyllamaMix 1.1B Benchmarks

ARC: 31.48 vs 96.7 (so35)-67.4%
HellaSwag: 48.39 vs 95.3 (gpt4)-49.2%
MMLU: 25.05 vs 88.3 (so35)-71.6%
TruthfulQA: 33.45 vs 59 (gpt4)-43.3%
WinoGrande: 58.48 vs 87.5 (gpt4)-33.2%
GSM8K: 1.06 vs 96.4 (so35)-98.9%
LLME Score: 0.16495
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
TinyllamaMix 1.1B (Aryanne/TinyllamaMix-1.1B)
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TinyllamaMix 1.1B Parameters and Internals

Model Type 
text-generation
Additional Notes 
This is a TinyLlama mix merge, experimental, using a custom merge method. Should be better at RP.
LLM NameTinyllamaMix 1.1B
Repository 🤗https://huggingface.co/Aryanne/TinyllamaMix-1.1B 
Base Model(s)  aegon-h/TinyLlama-1.1B   aegon-h/TinyLlama-1.1B
Model Size1.1b
Required VRAM2.2 GB
Updated2026-01-06
MaintainerAryanne
Model Typellama
Model Files  2.2 GB   2.0 GB: 1-of-2   0.2 GB: 2-of-2   1.2 GB
GGUF QuantizationYes
Quantization Typegguf|q8
Model ArchitectureLlamaForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.35.2
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than Aryanne/TinyllamaMix-1.1B.

Rank the TinyllamaMix 1.1B 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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