gguf-connector 3.2.9

GGUF connector(s) with GUI

GGUF connector

GGUF (GPT-Generated Unified Format) is a successor of GGML (GPT-Generated Model Language), it was released on August 21, 2023; by the way, GPT stands for Generative Pre-trained Transformer.

This package is a simple graphical user interface (GUI) application that uses the ctransformers or llama.cpp to interact with a chat model for generating responses.

Install the connector via pip (once only):

pip install gguf-connector

Update the connector (if previous version installed) by:

pip install gguf-connector --upgrade

With this version, you can interact straight with the GGUF file(s) available in the same directory by a simple command.

Graphical User Interface (GUI)

Select model(s) with ctransformers (optional: need ctransformers to work; pip install ctransformers):

ggc c

Select model(s) with llama.cpp connector (optional: need llama-cpp-python to work; get it here or nightly here):

ggc cpp

Command Line Interface (CLI)

Select model(s) with ctransformers:

ggc g

Select model(s) with llama.cpp connector:

ggc gpp

Select model(s) with vision connector:

ggc v

Opt a clip handler then opt a vision model; prompt your picture link to process (see example here)

Metadata reader (CLI only)

Select model(s) with metadata reader:

ggc r

Select model(s) with metadata fast reader:

ggc r2

Select model(s) with tensor reader (optional: need torch to work; pip install torch):

ggc r3

PDF analyzor (beta feature on CLI recently)

Load PDF(s) into a model with ctransformers:

ggc cp

Load PDF(s) into a model with llama.cpp connector:

ggc pp

optional: need pypdf; pip install pypdf

Speech recognizor (beta feature; accept WAV format recently)

Prompt WAV(s) into a model with ctransformers:

ggc cs

Prompt WAV(s) into a model with llama.cpp connector:

ggc ps

optional: need speechrecognition, pocketsphinx; pip install speechrecognition, pocketsphinx

Speech recognizor (via Google api; online)

Prompt WAV(s) into a model with ctransformers:

ggc cg

Prompt WAV(s) into a model with llama.cpp connector:

ggc pg

Container

Launch to page/container:

ggc w

Divider

Divide gguf into different part(s) with a cutoff point (size):

ggc d2

Merger

Merge all gguf into one:

ggc m2

Merger (safetensors)

Merge all safetensors into one (optional: need torch to work; pip install torch):

ggc ma

Splitter (checkpoint)

Split checkpoint into components (optional: need torch to work; pip install torch):

ggc s

Quantizor

Quantize safetensors to fp8 (downscale; optional: need torch to work; pip install torch):

ggc q

Quantize safetensors to fp32 (upscale; optional: need torch to work; pip install torch):

ggc q2

Convertor

Convert safetensors to gguf (auto; optional: need torch to work; pip install torch):

ggc t

Convertor (alpha)

Convert safetensors to gguf (meta; optional: need torch to work; pip install torch):

ggc t1

Convertor (beta)

Convert safetensors to gguf (unlimited; optional: need torch to work; pip install torch):

ggc t2

Convertor (gamma)

Convert gguf to safetensors (reversible; optional: need torch to work; pip install torch):

ggc t3

Swapper (lora)

Rename lora tensor (base/unet swappable; optional: need torch to work; pip install torch):

ggc la

Remover

Tensor remover:

ggc rm

Renamer

Tensor renamer:

ggc rn

Extractor

Tensor extractor:

ggc ex

Cutter

Get cutter for bf/f16 to q2-q8 quantization (see user guide here) by:

ggc u

Comfy

Download comfy pack (see user guide here) by:

ggc y

Node

Clone node (see user/setup guide here) by:

ggc n

Pack

Take pack (see user guide here) by:

ggc p

PackPack

Take packpack (see user guide here) by:

ggc p2

FramePack (1-click long video generation)

Take framepack (portable packpack) by:

ggc p1

Run framepack - ggc edition by (optional: need framepack to work; pip install framepack):

ggc f2

Smart contract generator (solidity)

Activate backend and frontend by (optional: need transformers to work; pip install transformers):

ggc g1

Video 1 (image to video)

Activate backend and frontend by (optional: need torch, diffusers to work; pip install torch, diffusers):

ggc v1

Video 2 (text to video)

Activate backend and frontend by (optional: need torch, diffusers to work; pip install torch, diffusers):

ggc v2

Image 2 (text to image)

Activate backend and frontend by (optional: need torch, diffusers to work; pip install torch, diffusers):

ggc i2

Kontext 2 (image editor)

Activate backend and frontend by (optional: need torch, diffusers to work; pip install torch, diffusers):

ggc k2

With lora selection:

ggc k1

With memory economy mode (low/no vram or w/o gpu option):

ggc k3

Krea 4 (image generator)

Activate backend and frontend by (optional: need torch, diffusers to work; pip install torch, diffusers):

ggc k4

Note 2 (OCR)

Activate backend and frontend by (optional: need transformers to work; pip install transformers):

ggc n2

Image descriptor (image to text)

Activate backend and frontend by (optional: need torch to work; pip install torch):

ggc f5

Realtime live captioning:

ggc f7

Connector mode, opt a gguf to interact with (see example here):

ggc f6

Activate accurate/precise mode by (optional: need vtoo to work; pip install vtoo):

ggc h3

Opt a model file to interact with (see example here)

Speech 2 (text to speech)

Activate backend and frontend by (optional: need diao to work; pip install diao):

ggc s2

Higgs 2 (text to audio)

Activate backend and frontend by (optional: need higgs to work; pip install higgs):

ggc h2

Multilingual supported, i.e., Spanish, German, Korean, etc.

Bagel 2 (any to any)

Activate backend and frontend by (optional: need bagel2 to work; pip install bagel2):

ggc b2

Opt a vae then opt a model file (see example here)

Voice 2 (text to voice)

Activate backend and frontend by (optional: need chichat to work; pip install chichat):

ggc c2

Opt a vae, a clip (t3-cfg) and a model file (see example here)

Voice 3 (text to voice)

Multilingual (optional: need chichat to work; pip install chichat):

ggc c3

Opt a vae, a clip (t3-23lang) and a model file (see example here)

Audio 2 (text to audio)

Activate backend and frontend by (optional: need fishaudio to work; pip install fishaudio):

ggc o2

Opt a codec then opt a model file (see example here)

Krea 7 (image generator)

Activate backend and frontend by (optional: need dequantor to work; pip install dequantor):

ggc k7

Opt a model file in the current directory (see example here)

Kontext 8 (image editor)

Activate backend and frontend by (optional: need dequantor to work; pip install dequantor):

ggc k8

Opt a model file in the current directory (see example here)

Flux connector (all-in-one)

Select flux image model(s) with k connector:

ggc k

Qwen image connector

Select qwen image model(s) with q5 connector:

ggc q5

Opt a model file to interact with (see example here)

Qwen image edit connector

Select image edit model(s) with q6 connector:

ggc q6

Opt a model file to interact with (see example here)

Qwen image edit plus connector

Select image edit plus model(s) with q7 connector:

ggc q7

Qwen image edit plux connector - multiple image input

Select image edit plus model(s) with q8 connector:

ggc q8

Opt a model file to interact with (see example here)

Qwen image edit ++ connector - multiple image input

Select image edit plus/lite model(s) with q9 connector (need nunchaku to work; get it here):

ggc q9

Opt a scaled 4-bit safetensors model file to interact with

Qwen image lite connector - multiple image input

Select image edit lite model(s) with q0 connector:

ggc q0

Qwen image lite2 connector - multiple image input

Select image edit lite2 model(s) with p0 connector:

ggc p0

Qwen image lite3 connector - multiple image input

Select image edit lite3 model(s) with p9 connector:

ggc p9

Z image connector

Select z image model(s) with z1 connector:

ggc z1

Lumina image connector

Select lumina image model(s) with l2 connector:

ggc l2

Wan video connector

Select wan video model(s) with w2 connector:

ggc w2

Ltxv connector

Select ltxv model(s) with x2 connector:

ggc x2

Mochi connector

Select mochi model(s) with m1 connector:

ggc m1

Kx-lite connector

Select kontext model(s) with k0 connector:

ggc k0

Opt a model file to interact with (see example here)

SD-lite connector

Select sd3.5 model(s) with s3 connector:

ggc s3

Opt a model file to interact with (see example here)

Higgs audio connector

Select higgs model(s) with h6 connector:

ggc h6

Opt a model file to interact with (see example here)

Dia connector (text to speech)

Select dia model(s) with s6 connector:

ggc s6

Opt a model file to interact with (see example here)

FastVLM connector (image-text to text)

Select fastvlm model(s) with f9 connector:

ggc f9

Opt a model file to interact with (see example here)

VibeVoice connector (text/voice to speech)

Select vibevoice model(s) with v6 connector (optional: need yvoice to work; pip install yvoice):

ggc v6

Opt a model file to interact with (see example here)

Docling connector (image/document to text)

Select docling model(s) with n3 connector:

ggc n3

Opt a model file to interact with (see example here)

Gudio (text to speech)

Activate backend and frontend by (optional: need gudio to work; pip install gudio):

ggc g2

Opt a model then opt a clip (see example here)

Sketch (draw something awesome)

Sketch gguf connector (optional: need dequantor to work; pip install dequantor):

ggc s8

Sketch safetensors connector (optional: need nunchaku to work; get it here):

ggc s9

Opt a model file to interact with (see example here)

Studio

Studio connector:

ggc w9

Opt a recognizor, a generator, and a transformer to interact with (see example here)

api (self-hosted backend)

Fast sd3.5 connector:

ggc w8

Fast lumina connector:

ggc w7

Fast flux connector:

ggc w6

Frontend test.gguf.org or localhost (open a new console/terminal: ggc b)

api (self-hosted backend) - exclusive for 🐷 holder trial recently

Fast image-to-video connector:

ggc e5

Fast video connector:

ggc e6

Fast scan connector:

ggc e7

Fast edit connector:

ggc e8

Fast plus connector:

ggc e9

Frontend gguf.org or localhost (open a new console/terminal: ggc a)

chatpig - GPT like frontend and backend

Frontend chatpig launcher:

ggc b4

Backend chatpig connector (optional: need llama-cpp-python to work):

ggc e4

Opt any gguf model to load (text-based generation)

cli chatbot

Launcher:

ggc l

computer use 🤖🕹️

Computer use agent (optional: need gguf-cua to work; pip install gguf-cua):

ggc cu

Get the model file(s) here for backend

vibe code 👾🎮

Vibe code agent (optional: need coder to work; npm install -g @gguf/coder):

ggc vc

Menu

Enter the main menu for selecting a connector or getting pre-trained trial model(s).

ggc m

Import as a module

Include the connector selection menu to your code by:

from gguf_connector import menu

For standalone version please refer to the repository in the reference list (below).

References

model selector (standalone version: installable package)

cgg (cmd-based tool)

Resources

ctransformers llama.cpp

Article

understanding gguf and the gguf-connector

Website

gguf.org (you can download the frontend from github and host it locally; the backend is ethereum blockchain)

gguf.io (i/o is a mirror of us; note: this web3 domain might be restricted access in some regions/by some service providers, if so, visit the one above/below instead, exactly the same)

gguf.us