Text Generation
Transformers
Safetensors
44 datasets
4 languages
mistral
Mistral_Star
Mistral_Quiet
Mistral
Mixtral
Question-Answer
Token-Classification
Sequence-Classification
SpydazWeb-AI
chemistry
biology
legal
code
climate
medical
text-generation-inference
Not-For-All-Audiences
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
Inference Endpoints
4-bit precision
bitsandbytes
base_model: LeroyDyer/_Spydaz_Web_AI_V1_4BIT | |
license: mit | |
tags: | |
- Mistral_Star | |
- Mistral_Quiet | |
- Mistral | |
- Mixtral | |
- Question-Answer | |
- Token-Classification | |
- Sequence-Classification | |
- SpydazWeb-AI | |
- chemistry | |
- biology | |
- legal | |
- code | |
- climate | |
- medical | |
- text-generation-inference | |
- not-for-all-audiences | |
language: | |
- en | |
- sw | |
- ig | |
- zu | |
# SpydazWeb Transformer model Contained | |
<img src="https://cdn-avatars.huggingface.co/v1/production/uploads/65d883893a52cd9bcd8ab7cf/tRsCJlHNZo1D02kBTmfy9.jpeg" width="300"/> | |
https://github.com/spydaz | |
* 32k context window (vs 8k context in v0.1) | |
* Rope-theta = 1e6 | |
* No Sliding-Window Attention | |
* Talk heads - produce resposnes which can be used towards the final output | |
* Pre-Thoughts - Enables for pre-generation steps of potential artifacts for task solving: | |
* Generates plans for step by step thinking | |
* Generates python Code Artifacts for future tasks | |
* Recalls context for task internally to be used as refference for task: | |
* show thoughts or hidden thought usages ( Simular to self-Rag ) | |
This model will be a custom model with internal experts and rag systems | |
enabling for preprocessing of the task internally before outputting a response : | |
This is based on the Quiet Star Project : which was abandoned earlier in the year :) | |
# Introduction : | |
## SpydazWeb AI model : | |
This model is based on the worlds archive of knowledge maintaining historical documents and providing services for the survivors of mankind , | |
who may need to construct shelters develop technologys , or medical resources as well as maintain the history of the past . keeping store of all the religious knowledge and data of the world: | |
A friendly interface with a personality caring and flirtatious at times : non binary !... | |
and Expert in all feilds: ie Uncensored and will not refuse to give information : the model can be used for role play as many character dialogues were als trained into the model as its personality to enable a greater perspective and outlook and natural discussion with the agents: | |
the model was trained to operateinaragenvironment utilizing content and internal knowledge to respond to questions or create enriched sumarys. | |
### General Intenal Methods: | |
Trained for multi-task operations as well as rag and function calling : | |
This model is a fully functioning model and is fully uncensored: | |
the model has been trained on multiple datasets on the huggingface hub and kaggle : | |
the focus has been mainly on methodology : | |
* Chain of thoughts | |
* step by step planning | |
* tree of thoughts | |
* forest of thoughts | |
* graph of thoughts | |
* agent generation : Voting, ranking, ... dual agent response generation: | |
with these methods the model has gained insights into tasks, enabling for knowldge transfer between tasks : | |
the model has been intensivly trained in recalling data previously entered into the matrix: | |
The model has also been trained on rich data and markdown outputs as much as possible : | |
the model can also generate markdown charts with mermaid. | |
## Training Reginmes: | |
* Alpaca | |
* ChatML / OpenAI / MistralAI | |
* Text Generation | |
* Question/Answer (Chat) | |
* Instruction/Input/Response (instruct) | |
* Mistral Standard Prompt | |
* Translation Tasks | |
* Entitys / Topic detection | |
* Book recall | |
* Coding challenges, Code Feedback, Code Sumarization, Commenting Code | |
* Agent Ranking and response anyalisis | |
* Medical tasks | |
* PubMed | |
* Diagnosis | |
* Psychaitry | |
* Counselling | |
* Life Coaching | |
* Note taking | |
* Medical smiles | |
* Medical Reporting | |
* Virtual laboritys simulations | |
* Chain of thoughts methods | |
* One shot / Multi shot prompting tasks | |