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Mistroll 7B V2.2 by BarraHome

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  Autotrain compatible Base model:quantized:yam-peleg... Base model:yam-peleg/experimen...   Conversational   En   Endpoints compatible   Es   Gguf   Mistral   Q8   Quantized   Region:us   Safetensors   Sharded   Tensorflow   Unsloth
Model Card on HF 🤗: https://huggingface.co/BarraHome/Mistroll-7B-v2.2 

Mistroll 7B V2.2 Benchmarks

ARC: 72.78 vs 96.7 (so35)-24.7%
HellaSwag: 89.16 vs 95.3 (gpt4)-6.4%
MMLU: 64.35 vs 88.3 (so35)-27.1%
TruthfulQA: 78.1 vs 59 (gpt4)32.4%
WinoGrande: 85 vs 87.5 (gpt4)-2.9%
GSM8K: 71.19 vs 96.4 (so35)-26.2%
LLME Score: 0.23853
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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Mistroll 7B V2.2 Parameters and Internals

LLM NameMistroll 7B V2.2
Repository 🤗https://huggingface.co/BarraHome/Mistroll-7B-v2.2 
Base Model(s)  Experiment26 7B   yam-peleg/Experiment26-7B
Model Size7b
Required VRAM14.4 GB
Updated2025-06-09
MaintainerBarraHome
Model Typemistral
Model Files  7.7 GB   4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3
Supported Languagesen es
GGUF QuantizationYes
Quantization Typeq8|gguf
Model ArchitectureMistralForCausalLM
Licensemit
Context Length32768
Model Max Length32768
Transformers Version4.40.0
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32000
Torch Data Typebfloat16
Mistroll 7B V2.2 (BarraHome/Mistroll-7B-v2.2)

Quantized Models of the Mistroll 7B V2.2

Model
Likes
Downloads
VRAM
...troll 7B V2.3 NoTsOsm4rt 16bit0814 GB
...stroll 7B V2.3 NoTsOsm4rt Gguf075 GB

Best Alternatives to Mistroll 7B V2.2

Best Alternatives
Context / RAM
Downloads
Likes
MegaBeam Mistral 7B 300K Gguf282K / 5 GB113
Boptruth Agatha 7B32K / 14.4 GB1350
Mistral 7B Instruct V0.2.gguf32K / 14.5 GB303
Mistral 7B Instruct V0.2 GGUF32K / 4.4 GB242
...andle Mistral 7B Instruct V0.232K / 14.4 GB370
Mahou 1.2a Mistral 7B32K / 14.4 GB596
Moxin Chat 7B32K / 0.9 GB23632
Mistral V0.3 7B Cybersecurity32K / 14.5 GB371
BioMistralMerged32K / 14.4 GB45540
Moxin Llm 7B32K / 0.9 GB10015
Note: green Score (e.g. "73.2") means that the model is better than BarraHome/Mistroll-7B-v2.2.

Rank the Mistroll 7B V2.2 Capabilities

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Instruction Following and Task Automation  
Factuality and Completeness of Knowledge  
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Original data from HuggingFace, OpenCompass and various public git repos.
Release v20241124
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