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Mistral Llm V3 by Bharat05092003

 »  All LLMs  »  Bharat05092003  »  Mistral Llm V3   URL Share it on

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  4bit Base model:quantized:unsloth/m... Base model:unsloth/mistral-7b-...   En   Endpoints compatible   Gguf   Lora   Mistral   Quantized   Region:us   Safetensors   Trl   Unsloth
Model Card on HF 🤗: https://huggingface.co/Bharat05092003/mistral_llm_v3 

Mistral Llm V3 Benchmarks

LLME Score: 0.19069
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mistral Llm V3 (Bharat05092003/mistral_llm_v3)

Mistral Llm V3 Parameters and Internals

Model Type 
text-generation-inference, transformers, unsloth, mistral, trl
Additional Notes 
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
LLM NameMistral Llm V3
Repository 🤗https://huggingface.co/Bharat05092003/mistral_llm_v3 
Base Model(s)  Mistral 7B Bnb 4bit   unsloth/mistral-7b-bnb-4bit
Model Size7b
Required VRAM0.2 GB
Updated2025-01-31
MaintainerBharat05092003
Model Files  0.2 GB   4.4 GB
Supported Languagesen
GGUF QuantizationYes
Quantization Typegguf|4bit
Model ArchitectureAutoModel
Licenseapache-2.0
Model Max Length32768
Is Biasednone
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
PEFT TypeLORA
LoRA ModelYes
PEFT Target Moduleso_proj|up_proj|gate_proj|down_proj|k_proj|v_proj|q_proj
LoRA Alpha16
LoRA Dropout0
R Param16

Best Alternatives to Mistral Llm V3

Best Alternatives
Context / RAM
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Likes
Pixel8K / 4.4 GB170
Mistral 7B Instruct V0.3 GGUF0K / 1.6 GB145894479
Qwen2 7B Instruct GGUF0K / 1.9 GB103427911
WizardLM 2 7B GGUF0K / 2.7 GB132146676
Conversely Mistral 7B0K / 0.2 GB2820
Deepthink Reasoning 7B GGUF0K / 4.7 GB134111
CleverBoi 7B V20K / 0.1 GB3230
Mistral 7B Instruct V0.3 GGUF0K / 2.7 GB704629
Neumind Math 7B Instruct GGUF0K / 4.7 GB2749
QwQ LCoT 7B Instruct GGUF0K / 4.7 GB1879
Note: green Score (e.g. "73.2") means that the model is better than Bharat05092003/mistral_llm_v3.

Rank the Mistral Llm V3 Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

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
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