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Mistral 7B V0.1 Hitl by KasparZ

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  Autotrain compatible   Endpoints compatible   Gguf   Lora   Mistral   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/KasparZ/Mistral-7B-v0.1-hitl 

Mistral 7B V0.1 Hitl Benchmarks

ARC: 60.32 vs 96.7 (so35)-37.6%
HellaSwag: 83.37 vs 95.3 (gpt4)-12.5%
MMLU: 63.81 vs 88.3 (so35)-27.7%
TruthfulQA: 42.17 vs 59 (gpt4)-28.5%
WinoGrande: 78.06 vs 87.5 (gpt4)-10.8%
GSM8K: 37.07 vs 96.4 (so35)-61.5%
LLME Score: 0.1808
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Mistral 7B V0.1 Hitl (KasparZ/Mistral-7B-v0.1-hitl)

Mistral 7B V0.1 Hitl Parameters and Internals

Model Type 
CAUSAL_LM
Additional Notes 
Loading is set to 4-bit, specific target modules include 'q_proj', 'k_proj', 'v_proj', 'o_proj', 'gate_proj'.
Training Details 
Data Sources:
KasparZ/HITL-2
LLM NameMistral 7B V0.1 Hitl
Repository 🤗https://huggingface.co/KasparZ/Mistral-7B-v0.1-hitl 
Base Model(s)  Dbpedia   predibase/dbpedia
Model Size7b
Required VRAM14.4 GB
Updated2025-05-14
MaintainerKasparZ
Model Files  7.7 GB   0.4 GB   4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3
GGUF QuantizationYes
Quantization Typegguf
Model ArchitectureAutoModelForCausalLM
Is Biasednone
Tokenizer ClassLlamaTokenizer
Padding Token</s>
PEFT TypeLORA
LoRA ModelYes
PEFT Target Modulesq_proj|gate_proj|v_proj|o_proj|k_proj
LoRA Alpha16
LoRA Dropout0.1
R Param64

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Note: green Score (e.g. "73.2") means that the model is better than KasparZ/Mistral-7B-v0.1-hitl.

Rank the Mistral 7B V0.1 Hitl 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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