---
language:
- en
- sw
- ig
- so
- es
- ca
license: apache-2.0
metrics:
- accuracy
- bertscore
- bleu
- brier_score
- cer
- character
- charcut_mt
- chrf
- code_eval
tags:
- text-generation-inference
- transformers
- unsloth
- mistral
- trl
- code
- farmer
- doctor
- Mega-Series
- Cyber-Series
- Role-Play
- Self-Rag
- ThinkingBot
- milestone
- mega-series
- SpydazWebAI
- llama-cpp
- gguf-my-repo
base_model: LeroyDyer/_Spydaz_Web_AI_
---

# Uploaded  model

- **Developed by:** Leroy "Spydaz" Dyer
- **License:** apache-2.0
- **Finetuned from model :** LeroyDyer/LCARS_AI_010
[<img src="https://cdn-avatars.huggingface.co/v1/production/uploads/65d883893a52cd9bcd8ab7cf/tRsCJlHNZo1D02kBTmfy9.jpeg" width="300"/>
https://github.com/spydaz


* The Mistral-7B-Instruct-v0.2 Large Language Model (LLM) is an instruct fine-tuned version of the Mistral-7B-v0.2.

* Mistral-7B-v0.2 has the following changes compared to Mistral-7B-v0.1

    * 32k context window (vs 8k context in v0.1)
    * Rope-theta = 1e6
    * No Sliding-Window Attention


# Introduction :

## SpydazWeb AI model :

### 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
* steo by step
* tree of thoughts
* forest of thoughts
* graph of thoughts
* agent generation : Voting, ranking, ...

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:











This mistral model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.

[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)