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Jett W26 Abliterated by giannisan

 »  All LLMs  »  giannisan  »  Jett W26 Abliterated   URL Share it on

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  Arxiv:2306.01708   Arxiv:2311.03099   Autotrain compatible Base model:chihoonlee10/t3q-mi... Base model:inferenceillusionis... Base model:kukedlc/jupiter-k-7... Base model:merge:chihoonlee10/... Base model:merge:inferenceillu... Base model:merge:kukedlc/jupit... Base model:merge:s-miguel/the-... Base model:merge:senseable/wes... Base model:merge:yam-peleg/exp... Base model:s-miguel/the-trinit... Base model:senseable/westlake-... Base model:yam-peleg/experimen...   Codegen   Endpoints compatible   Instruct   Merge   Mergekit   Mistral   Region:us   Safetensors   Sharded   Tensorflow
Model Card on HF 🤗: https://huggingface.co/giannisan/Jett-w26-abliterated 

Jett W26 Abliterated Benchmarks

LLME Score: 0.15487
nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").
Jett W26 Abliterated (giannisan/Jett-w26-abliterated)
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Jett W26 Abliterated Parameters and Internals

Model Type 
pre-trained, language model
Additional Notes 
This model is a merge of several pre-trained models using the mergekit tool.
Training Details 
Methodology:
Merged using the DARE TIES merge method
LLM NameJett W26 Abliterated
Repository 🤗https://huggingface.co/giannisan/Jett-w26-abliterated 
Base Model(s)  T3Q Mistral Orca Math DPO   WestLake 7B V2   The Trinity Coder 7B   Experiment26 7B   Excalibur 7B DPO   Jupiter K 7B Slerp   chihoonlee10/T3Q-Mistral-Orca-Math-DPO   senseable/WestLake-7B-v2   S-miguel/The-Trinity-Coder-7B   yam-peleg/Experiment26-7B   InferenceIllusionist/Excalibur-7b-DPO   Kukedlc/Jupiter-k-7B-slerp
Model Size7b
Required VRAM14.4 GB
Updated2025-09-23
Maintainergiannisan
Model Typemistral
Instruction-BasedYes
Model Files  4.9 GB: 1-of-3   5.0 GB: 2-of-3   4.5 GB: 3-of-3
Generates CodeYes
Model ArchitectureMistralForCausalLM
Context Length32768
Model Max Length32768
Transformers Version4.41.2
Tokenizer ClassLlamaTokenizer
Padding Token<unk>
Vocabulary Size32000
Torch Data Typebfloat16

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Note: green Score (e.g. "73.2") means that the model is better than giannisan/Jett-w26-abliterated.

Rank the Jett W26 Abliterated 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 v20241124
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