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CollectiveCognition V1.1 Mistral 7B 5.0bpw H6 EXL2 by LoneStriker

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  Autotrain compatible Base model:finetune:nousresear... Base model:nousresearch/llama-... Dataset:collectivecognition/ch...   Distillation   En   Endpoints compatible   Exl2   Finetuned   Gpt4   Instruct   Mistral   Mistral-7b   Pytorch   Quantized   Region:us   Sharegpt   Synthetic data
Model Card on HF 🤗: https://huggingface.co/LoneStriker/CollectiveCognition-v1.1-Mistral-7B-5.0bpw-h6-exl2 

CollectiveCognition V1.1 Mistral 7B 5.0bpw H6 EXL2 Benchmarks

LLME Score: 0.10979
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
CollectiveCognition V1.1 Mistral 7B 5.0bpw H6 EXL2 (LoneStriker/CollectiveCognition-v1.1-Mistral-7B-5.0bpw-h6-exl2)
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CollectiveCognition V1.1 Mistral 7B 5.0bpw H6 EXL2 Parameters and Internals

Model Type 
instruct, finetune
Use Cases 
Areas:
research, commercial applications
Applications:
TruthfulQA assessments
Primary Use Cases:
Understanding and rectifying misconceptions
Additional Notes 
Trained on synthetic data, fast training time
Supported Languages 
en (Unknown proficiency)
Training Details 
Data Sources:
CollectiveCognition/chats-data-2023-09-27
Data Volume:
100 data points
Methodology:
Mistral approach, qlora
Training Time:
3 minutes
Hardware Used:
single 4090
Input Output 
Input Format:
USER: ASSISTANT:
Accepted Modalities:
text
Output Format:
text
LLM NameCollectiveCognition V1.1 Mistral 7B 5.0bpw H6 EXL2
Repository 🤗https://huggingface.co/LoneStriker/CollectiveCognition-v1.1-Mistral-7B-5.0bpw-h6-exl2 
Base Model(s)  Llama 2 13B Hf   NousResearch/Llama-2-13b-hf
Model Size13b
Required VRAM4.7 GB
Updated2025-10-16
MaintainerLoneStriker
Model Typemistral
Model Files  4.7 GB
Supported Languagesen
Quantization Typeexl2
Model ArchitectureMistralForCausalLM
Licenseapache-2.0
Context Length32768
Model Max Length32768
Transformers Version4.34.0.dev0
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typefloat16

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Note: green Score (e.g. "73.2") means that the model is better than LoneStriker/CollectiveCognition-v1.1-Mistral-7B-5.0bpw-h6-exl2.

Rank the CollectiveCognition V1.1 Mistral 7B 5.0bpw H6 EXL2 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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