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BagelMIsteryTour V2 8x7B 4.5bpw H6 EXL2 by JayhC

 »  All LLMs  »  JayhC  »  BagelMIsteryTour V2 8x7B 4.5bpw H6 EXL2   URL Share it on

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  Merged Model   Arxiv:2306.01708   Arxiv:2311.03099   Autotrain compatible Base model:doctor-shotgun/lima... Base model:jondurbin/bagel-dpo... Base model:mistralai/mixtral-8... Base model:mistralai/mixtral-8... Base model:sao10k/sensualize-m...   Endpoints compatible   Exl2   Instruct   Mixtral   Moe   Quantized   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/JayhC/BagelMIsteryTour-v2-8x7B-4.5bpw-h6-exl2 

BagelMIsteryTour V2 8x7B 4.5bpw H6 EXL2 Benchmarks

LLME Score: 0.18434
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
BagelMIsteryTour V2 8x7B 4.5bpw H6 EXL2 (JayhC/BagelMIsteryTour-v2-8x7B-4.5bpw-h6-exl2)

BagelMIsteryTour V2 8x7B 4.5bpw H6 EXL2 Parameters and Internals

Model Type 
text generation
Additional Notes 
Works well with Alpaca and Mistral prompt formats.
Training Details 
Methodology:
DARE and TIES merge methods were used.
Input Output 
Input Format:
Instruction/Response, and Instruction/Input/Response formats.
Accepted Modalities:
text
Output Format:
varied text responses
Performance Tips:
May require additional tuning for specific prompt formats, such as adding a stopping string for RP to avoid repetition.
Release Notes 
Version:
v2
Notes:
Lowered the mix of Sensualize component in the model.
LLM NameBagelMIsteryTour V2 8x7B 4.5bpw H6 EXL2
Repository 🤗https://huggingface.co/JayhC/BagelMIsteryTour-v2-8x7B-4.5bpw-h6-exl2 
Base Model(s)  mistralai/Mixtral-8x7B-v0.1   jondurbin/bagel-dpo-8x7b-v0.2   Sensualize Mixtral Bf16   mistralai/Mixtral-8x7B-v0.1   ...imarp Zloss Mixtral 8x7b Qlora   mistralai/Mixtral-8x7B-Instruct-v0.1   mistralai/Mixtral-8x7B-v0.1   jondurbin/bagel-dpo-8x7b-v0.2   Sao10K/Sensualize-Mixtral-bf16   mistralai/Mixtral-8x7B-v0.1   Doctor-Shotgun/limarp-zloss-mixtral-8x7b-qlora   mistralai/Mixtral-8x7B-Instruct-v0.1
Merged ModelYes
Required VRAM26.5 GB
Updated2024-12-26
MaintainerJayhC
Model Typemixtral
Instruction-BasedYes
Model Files  8.6 GB: 1-of-4   8.6 GB: 2-of-4   8.6 GB: 3-of-4   0.7 GB: 4-of-4
Quantization Typeexl2
Model ArchitectureMixtralForCausalLM
Licensecc-by-nc-4.0
Context Length32768
Model Max Length32768
Transformers Version4.36.2
Tokenizer ClassLlamaTokenizer
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than JayhC/BagelMIsteryTour-v2-8x7B-4.5bpw-h6-exl2.

Rank the BagelMIsteryTour V2 8x7B 4.5bpw 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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Release v20241227
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