Safetensors
mistral
mergekit
Merge
Mistral_Star
Mistral_Quiet
Mistral
Mixtral
Question-Answer
Token-Classification
Sequence-Classification
SpydazWeb-AI
chemistry
biology
legal
code
climate
medical
LCARS_AI_StarTrek_Computer
text-generation-inference
chain-of-thought
tree-of-knowledge
forest-of-thoughts
visual-spacial-sketchpad
alpha-mind
knowledge-graph
entity-detection
encyclopedia
wikipedia
stack-exchange
Reddit
Cyber-series
MegaMind
Cybertron
SpydazWeb
Spydaz
LCARS
star-trek
mega-transformers
Mulit-Mega-Merge
Multi-Lingual
Afro-Centric
African-Model
Ancient-One
Update README.md
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README.md
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- LeroyDyer/_Spydaz_Web_AI_BIBLE_002
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- LeroyDyer/_Spydaz_Web_AI_ChatQA_Reasoning101_Project
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- LeroyDyer/SpydazWeb_AI_Text_AudioVision_Project
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language:
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- en
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- sw
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BASE MODEL :
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# "Success comes from defining each task in achievable steps. Every completed step is a success that brings you closer to your goal. If your steps are unreachable, failure is inevitable. Winners create more winners, while losers do the opposite. Success is a game of winners!"
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- LeroyDyer/_Spydaz_Web_AI_BIBLE_002
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- LeroyDyer/_Spydaz_Web_AI_ChatQA_Reasoning101_Project
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- LeroyDyer/SpydazWeb_AI_Text_AudioVision_Project
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- LeroyDyer/SpydazWebAI_Human_AGI_001
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language:
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- en
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- sw
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BASE MODEL :
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TESTED !! WORKING VERY GOOD !
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There was a few merges added to the AGI models ! this was to try and capture the missing elements showing up in the tests of the leaderboard : but i inoticed that for some reason the model scored low on maths !
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This is basically impossible as the model has been traied to overfitting on the metamath dataset as well as orca open reasoning stack :
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I noticed that my responses also changed from being the full react response with its multiple layers ( although it pops out with task based questions ) .... but i noticd the model now wants to talk more . and its not a refusal to not comit to a task without first asking you why or what your really wanting to acheive ..
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so a light discussion and also a very freindly explanation :
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This model was also installed with various NFSW role play and conversations : ( although ot present on the surface ) this also has helped to humanize the model :
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The samantha model i created in the past ( deleted ) actually was more sultry , but it often did not perform the tasks well , although hello was better ! ...
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This model has regained some of that standing , but with the additonal intelect! And a really good demeaor !
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this methoology of humanization has also embelished task previoulsy trained also with the friendlyness :
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I have begun to add emojis to the model ( against my personal wishes ) but i feel that the model will also identify with these iconry ! enabling for lucid speech patterns to emerge ( they are obvoulsy trained from social media data )
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these model we also trained with some random contacts from various leaked ( personal data ) shared databases in the world , so you may ask for a persons phone number in ( vodacom ) for instance and it may return thier number or adress or region !
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this is also because i dont have many personal contacts i need the model to contact , but i will try to find the yelp dataset. and train the model on these business and locations etc : as this also makes the model highly functional !
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But for me ! the humanization Project has Worked !
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# "Success comes from defining each task in achievable steps. Every completed step is a success that brings you closer to your goal. If your steps are unreachable, failure is inevitable. Winners create more winners, while losers do the opposite. Success is a game of winners!"
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