Test by rom1leco

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  Arxiv:1910.09700   4bit   Autotrain compatible   Conversational   Endpoints compatible   Mistral   Pytorch   Quantized   Region:us   Sft   Sharded   Trl   Unsloth
Model Card on HF ๐Ÿค—: https://huggingface.co/rom1leco/test 

Test Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
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Test Parameters and Internals

LLM NameTest
Repository ๐Ÿค—https://huggingface.co/rom1leco/test 
Base Model(s)  Test2   alnrg2arg/test2
Model Size7b
Required VRAM14.4 GB
Updated2025-06-10
Maintainerrom1leco
Model Typemistral
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3
Quantization Type4bit
Model ArchitectureMistralForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.41.2
Tokenizer ClassLlamaTokenizer
Padding Token[control_768]
Vocabulary Size32000
Torch Data Typefloat16
Test (rom1leco/test)

Best Alternatives to Test

Best Alternatives
Context / RAM
Downloads
Likes
...al Nemo Instruct 2407 Bnb 4bit128K / 8.3 GB20816327
...istral Nemo Base 2407 Bnb 4bit128K / 8.3 GB226517
...t 3.5 0106 128K 4.0bpw H6 EXL2128K / 3.9 GB231
...t 3.5 0106 128K 8.0bpw H8 EXL2128K / 7.4 GB221
...tral 7B Instruct V0.3 Bnb 4bit32K / 4.1 GB6194428
Mistral 7B V0.3 Bnb 4bit32K / 4.1 GB2397016
Mistral 7B Instruct V0.2 Fp1632K / 14.4 GB260
...tral 7B Instruct V0.2 Bnb 4bit32K / 4.1 GB2666932
Mistral 7B Instruct V0.2 4bit32K / 4.3 GB2281
Mixtral V0.3 Full 16bit32K / 14.5 GB90
Note: green Score (e.g. "73.2") means that the model is better than rom1leco/test.

Rank the Test 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