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Test Mix 01 by appvoid

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Test Mix 01 is an open-source language model by appvoid. Features: 1.1b LLM, VRAM: 2.2GB, Context: 32K, Merged, LLM Explorer Score: 0.13.

  Merged Model   Arxiv:2306.01708   Base model:appvoid/palmer-003   Base model:appvoid/palmer-004 Base model:josephgflowers/tiny...   Endpoints compatible   Llama   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/appvoid/test-mix-01 

Test Mix 01 Benchmarks

LLME Score: 0.13352
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Test Mix 01 (appvoid/test-mix-01)
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Test Mix 01 Parameters and Internals

Model Type 
language model, merged
Additional Notes 
This is a merge of pre-trained language models created using mergekit.
Training Details 
Methodology:
TIES merge method
LLM NameTest Mix 01
Repository 🤗https://huggingface.co/appvoid/test-mix-01 
Base Model(s)  Palmer 003   Palmer 004 2406   TinyLlama Cinder Agent V1   appvoid/palmer-003   appvoid/palmer-004-2406   Josephgflowers/TinyLlama-Cinder-Agent-v1
Merged ModelYes
Model Size1.1b
Required VRAM2.2 GB
Updated2026-05-01
Maintainerappvoid
Model Typellama
Model Files  2.2 GB: 1-of-1
Model ArchitectureLlamaForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.41.0
Tokenizer ClassLlamaTokenizer
Padding Token</s>
Vocabulary Size32000
Torch Data Typefloat16

Best Alternatives to Test Mix 01

Best Alternatives
Context / RAM
Downloads
Likes
TinyKiller NSFW DPO 1.1B32K / 2.2 GB120
Coven Tiny 1.1b 32k Orpo Alpha32K / 2.2 GB122
Palmer Merge Test 532K / 2.2 GB50
TinyLlama 1.1B 32K32K / 2.2 GB92230
TinyLlama 1.1B 32K Instruct32K / 2.2 GB88713
...llama 1.1B 16K Instructions V432K / 2.2 GB80
TinyJ.O.S.I.E. 1.1B 32K Base32K / 2.2 GB301
Palmer 002 32K32K / 2.2 GB120
TinyJ.O.S.I.E. 1.1B 32K Base32K / 2.2 GB51
...lama 1.1B 16K Instructions Rag32K / 2.2 GB250
Note: green Score (e.g. "73.2") means that the model is better than appvoid/test-mix-01.

Rank the Test Mix 01 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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