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yrrhall/medit-xl-F16-GGUF overview

aynig/medit xl F16 GGUF This LoRA adapter was converted to GGUF format from grammarly/medit xl https://huggingface.co/grammarly/medit xl via the ggml.ai's GGUF…

transformersggufllama-cppgguf-my-loratext2text-generationendeesarjakozhdataset:wi_locnessdataset:matejklemen/falko_merlindataset:pawsdataset:paws-xdataset:assetbase_model:grammarly/medit-xlbase_model:quantized:grammarly/medit-xllicense:cc-by-nc-sa-4.0endpoints_compatibleregion:us

Runs locally from ~32.0 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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Pipeline
text-generation
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Repository Files & Downloads

1 GGUF files detected
Direct downloads for local inference
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medit-xl-f16.ggufGGUFF1632.0 MBDownload

Model Details

Model IDyrrhall/medit-xl-F16-GGUF
Authoryrrhall
Pipelinetext-generation
Licensecc-by-nc-sa-4.0
Base modelgrammarly/medit-xl
Last modified2026-07-17T20:42:36.000Z

Model README

---

license: cc-by-nc-sa-4.0

datasets:

  • wi_locness
  • matejklemen/falko_merlin
  • paws
  • paws-x
  • asset

language:

  • en
  • de
  • es
  • ar
  • ja
  • ko
  • zh

metrics:

  • bleu
  • rouge
  • sari
  • accuracy

library_name: transformers

widget:

  • text: 'Umschreiben sie den satz: When I grow up, I start to understand what he said

is quite right.'

example_title: GEC (de|en)

  • text: '문장의 간단한 버전 작성: Cuando se pueden mantener tasas de flujo comparables, los

resultados son altos.'

example_title: Simplification (ko|es)

  • text: 'Paraphrase this: いちごは物語を紹介し、読者をイベントに導くと彼は言った。'

example_title: Paraphrase (en|ja)

pipeline_tag: text2text-generation

base_model: grammarly/medit-xl

tags:

  • llama-cpp
  • gguf-my-lora

---

aynig/medit-xl-F16-GGUF

This LoRA adapter was converted to GGUF format from grammarly/medit-xl via the ggml.ai's GGUF-my-lora space.

Refer to the original adapter repository for more details.

Use with llama.cpp

# with cli
llama-cli -m base_model.gguf --lora medit-xl-f16.gguf (...other args)

# with server
llama-server -m base_model.gguf --lora medit-xl-f16.gguf (...other args)

To know more about LoRA usage with llama.cpp server, refer to the llama.cpp server documentation.

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