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MwM 22B Instruct by qingy2024

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  4bit   Autotrain compatible Base model:finetune:unsloth/mi... Base model:unsloth/mistral-sma...   Conversational   En   Endpoints compatible   Instruct   Mistral   Quantized   Region:us   Safetensors   Sharded   Tensorflow   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/qingy2024/MwM-22B-Instruct 

MwM 22B Instruct Benchmarks

LLME Score: 0.23542
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
MwM 22B Instruct (qingy2024/MwM-22B-Instruct)

MwM 22B Instruct Parameters and Internals

LLM NameMwM 22B Instruct
Repository 🤗https://huggingface.co/qingy2024/MwM-22B-Instruct 
Base Model(s)  ...l Small Instruct 2409 Bnb 4bit   unsloth/Mistral-Small-Instruct-2409-bnb-4bit
Model Size22b
Required VRAM44.7 GB
Updated2025-03-15
Maintainerqingy2024
Model Typemistral
Instruction-BasedYes
Model Files  4.9 GB: 1-of-9   5.0 GB: 2-of-9   5.0 GB: 3-of-9   4.9 GB: 4-of-9   5.0 GB: 5-of-9   5.0 GB: 6-of-9   4.9 GB: 7-of-9   5.0 GB: 8-of-9   5.0 GB: 9-of-9
Supported Languagesen
Quantization Type4bit
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length131072
Model Max Length131072
Transformers Version4.47.1
Tokenizer ClassLlamaTokenizer
Padding Token[control_748]
Vocabulary Size32768
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than qingy2024/MwM-22B-Instruct.

Rank the MwM 22B Instruct 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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Release v20241227
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