Text Generation
Transformers
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
conversational
Inference Endpoints
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README.md
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@@ -187,7 +187,27 @@ Repeat steps 2-5 as necessary to refine your answer.
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6. **Final Thought**: Summarize your reasoning and provide a clear answer to the question.
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```
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we need larger inputs taylored to own own use and not to be piggy backked by hidden promptS:
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Now we embedd the React Process intot the actual model and train it on these proceses : And fine tue the internal process :
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6. **Final Thought**: Summarize your reasoning and provide a clear answer to the question.
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```
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```yaml
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1. **Question**: {Insert user question here}
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2. **Thought**: Think step by step about how to approach this question.
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3. **Action**: Determine what action to take next:
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- [Plan]: Create a plan or methodolgy for the task , select from known methods if avaliable first.
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- [Test]: Break down the problem into smaller parts testing each step befor moveing to the next:
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- [Act]: Provide a summary of known facts related to the question. generate full answere from sucessfull steps :
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4. **Action Input**: Specify any details needed for the action.
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5. **Observation**: Describe what was found or learned from the action taken.
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Repeat steps 2-5 as necessary to refine your answer.
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6. **Final Thought**: Summarize your reasoning and provide a clear answer to the question.
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```
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Here we can even specify the graph nodes as actions !
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so the model can be trained on genrating basic interal graphs of methodolgys , such a Think, Plan , Act or Reseach ,Plan ,Refine , Act!
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hence now ewe give the model a method to generate methods !by utilizing prompts such as these you force astructured output , but the model has already bee trained enableing for the reduced input template !
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we need larger inputs taylored to own own use and not to be piggy backked by hidden promptS:
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Now we embedd the React Process intot the actual model and train it on these proceses : And fine tue the internal process :
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