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metadata
base_model: prithivMLmods/Megalodon-OCR-Sync-0713
language:
  - en
  - zh
library_name: transformers
mradermacher:
  readme_rev: 1
quantized_by: mradermacher
tags:
  - trl
  - text-generation-inference
  - image-captioning
  - optical-character-recognition
  - intelligent-character-recognition
  - caption
  - ocr
  - visual-understanding
  - art
  - icr
  - image-to-text
  - vlm
  - table
  - document

About

static quants of https://huggingface.co/prithivMLmods/Megalodon-OCR-Sync-0713

For a convenient overview and download list, visit our model page for this model.

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Megalodon-OCR-Sync-0713-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 mmproj-Q8_0 0.9 multi-modal supplement
GGUF Q2_K 1.4
GGUF mmproj-f16 1.4 multi-modal supplement
GGUF Q3_K_S 1.6
GGUF Q3_K_M 1.7 lower quality
GGUF Q3_K_L 1.8
GGUF IQ4_XS 1.9
GGUF Q4_K_S 1.9 fast, recommended
GGUF Q4_K_M 2.0 fast, recommended
GGUF Q5_K_S 2.3
GGUF Q5_K_M 2.3
GGUF Q6_K 2.6 very good quality
GGUF Q8_0 3.4 fast, best quality
GGUF f16 6.3 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.