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base_model: LeroyDyer/SpydazWebAI_Human_AGI
datasets:
  - neoneye/base64-decode-v2
  - neoneye/base64-encode-v1
  - VuongQuoc/Chemistry_text_to_image
  - Kamizuru00/diagram_image_to_text
  - LeroyDyer/Chemistry_text_to_image_BASE64
  - LeroyDyer/AudioCaps-Spectrograms_to_Base64
  - LeroyDyer/winogroud_text_to_imaget_BASE64
  - LeroyDyer/chart_text_to_Base64
  - LeroyDyer/diagram_image_to_text_BASE64
  - mekaneeky/salt_m2e_15_3_instruction
  - mekaneeky/SALT-languages-bible
language:
  - en
  - sw
  - ig
  - so
  - es
  - ca
  - xh
  - zu
  - ha
  - tw
  - af
  - hi
  - bm
  - su
library_name: transformers
license: apache-2.0
quantized_by: mradermacher
tags:
  - 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

About

static quants of https://huggingface.co/LeroyDyer/SpydazWebAI_Human_AGI

weighted/imatrix quants are available at https://huggingface.co/mradermacher/SpydazWebAI_Human_AGI-i1-GGUF

Usage

If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi-part files.

Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Link Type Size/GB Notes
GGUF Q2_K 2.8
GGUF Q3_K_S 3.3
GGUF Q3_K_M 3.6 lower quality
GGUF Q3_K_L 3.9
GGUF IQ4_XS 4.0
GGUF Q4_K_S 4.2 fast, recommended
GGUF Q4_K_M 4.5 fast, recommended
GGUF Q5_K_S 5.1
GGUF Q5_K_M 5.2
GGUF Q6_K 6.0 very good quality
GGUF Q8_0 7.8 fast, best quality
GGUF f16 14.6 16 bpw, overkill

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

image.png

And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time. Additional thanks to @nicoboss for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.