Mistral V0.3 Instruct Matter Slim A by munish0838

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  4bit   Autotrain compatible Base model:finetune:unsloth/mi... Base model:unsloth/mistral-7b-...   Conversational   En   Endpoints compatible   Instruct   Mistral   Pytorch   Quantized   Region:us   Safetensors   Sft   Sharded   Tensorflow   Trl   Unsloth

Mistral V0.3 Instruct Matter Slim A Benchmarks

nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mistral V0.3 Instruct Matter Slim A (munish0838/Mistral-v0.3-Instruct-Matter-Slim-A)

Mistral V0.3 Instruct Matter Slim A Parameters and Internals

Model Type 
text-generation-inference
Additional Notes 
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
Supported Languages 
en (full support)
Training Details 
Data Sources:
0-hero/Matter-0.1-Slim-A
LLM NameMistral V0.3 Instruct Matter Slim A
Repository ๐Ÿค—https://huggingface.co/munish0838/Mistral-v0.3-Instruct-Matter-Slim-A 
Base Model(s)  unsloth/mistral-7b-instruct-v0.3-bnb-4bit   unsloth/mistral-7b-instruct-v0.3-bnb-4bit
Model Size7b
Required VRAM14.5 GB
Updated2024-12-27
Maintainermunish0838
Model Typemistral
Instruction-BasedYes
Model Files  5.0 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3   5.0 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3
Supported Languagesen
Quantization Type4bit
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.41.2
Tokenizer ClassLlamaTokenizer
Padding Token[control_768]
Vocabulary Size32768
Torch Data Typefloat16

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Rank the Mistral V0.3 Instruct Matter Slim A 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 v20241227