Mistral 2 Law Adapter by wwgd

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Mistral 2 Law Adapter is an open-source language model by wwgd. Features: 7b LLM, VRAM: 28.9GB, Context: 32K, Instruction-Based, LLM Explorer Score: 0.15.

  Arxiv:1910.09700   Conversational   Endpoints compatible   Instruct   Mistral   Region:us   Safetensors   Sharded   Tensorflow

Mistral 2 Law Adapter Benchmarks

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

Mistral 2 Law Adapter Parameters and Internals

LLM NameMistral 2 Law Adapter
Repository 🤗https://huggingface.co/wwgd/mistral_2_law_adapter 
Model Size7b
Required VRAM28.9 GB
Updated2025-12-07
Maintainerwwgd
Model Typemistral
Instruction-BasedYes
Model Files  5.0 GB: 1-of-6   4.9 GB: 2-of-6   5.0 GB: 3-of-6   5.0 GB: 4-of-6   4.8 GB: 5-of-6   4.2 GB: 6-of-6
Model ArchitectureMistralForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.45.0.dev0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat32

Best Alternatives to Mistral 2 Law Adapter

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Context / RAM
Downloads
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...Nemo Instruct 2407 Abliterated1000K / 24.5 GB25420
SpydazWeb AI HumanAI RP512K / 14.4 GB241
SpydazWeb AI HumanAI 002512K / 14.4 GB181
...daz Web AI ChatML 512K Project512K / 14.5 GB120
... Summarize 64K QLoRANET Merged128K / 4.1 GB60
...1 Summarize 64K LoRANET Merged128K / 14.4 GB60
Mistral 7B Instruct V0.232K / 14.4 GB31562273149
Mistral 7B Instruct V0.132K / 14.4 GB3024581833
Mistral 7B Instruct V0.232K / 14.4 GB57590
Mistral Sk 7B Alpaca Slovak It32K / 13.4 GB4660
Note: green Score (e.g. "73.2") means that the model is better than wwgd/mistral_2_law_adapter.

Rank the Mistral 2 Law Adapter 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 v20260328a