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Theboukadida/laura-en-qwen3.5-2b-GGUF overview

Laura — German tutor in English Qwen3.5 2B, GGUF Laura is the tutor in an offline German course app for adult beginners A1–A2 . This model talks to the learner…

ggufqwen3.5germanlanguage-learningon-devicetext-generationdeenbase_model:Qwen/Qwen3.5-2Bbase_model:quantized:Qwen/Qwen3.5-2Blicense:apache-2.0endpoints_compatibleregion:usconversational

Runs locally from ~1.19 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).

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text-generation

Repository Files & Downloads

1 GGUF files detected
Direct downloads for local inference
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laura-en-qwen3.5-2b-Q4_K_M.ggufGGUFQ4_K_M1.19 GBDownload

Model Details

Model IDTheboukadida/laura-en-qwen3.5-2b-GGUF
AuthorTheboukadida
Pipelinetext-generation
Licenseapache-2.0
Base modelQwen/Qwen3.5-2B
Last modified2026-09-29T14:40:46.000Z

Model README

---

license: apache-2.0

base_model: Qwen/Qwen3.5-2B

language:

  • de
  • en

pipeline_tag: text-generation

tags:

  • gguf
  • qwen3.5
  • german
  • language-learning
  • on-device

---

Laura — German tutor in English (Qwen3.5 2B, GGUF)

Laura is the tutor in an offline German course app for adult beginners

(A1–A2). This model talks to the learner in English and teaches German with

German examples. It runs on the phone, CPU only.

This is a modified version of Qwen/Qwen3.5-2B.

Changes made: a LoRA adapter (rank 16, all linear layers, 2 epochs) was trained

on ~2,500–3,300 short tutoring conversations in English, merged into the weights,

and the result converted to GGUF and quantised to Q4_K_M with llama.cpp.

Distributed under the base model's Apache-2.0 licence.

How the app uses it

The app does not trust the model to judge German on its own. It checks the

learner's sentence with its own dictionary first and adds the verdict to the

message — (Check: ✗ → „corrected sentence“ · reason) or (Check: ✓ …) — plus

dictionary meanings and the chapter's rule card. The model was trained with

exactly those notes and explains them; without them it is a much weaker teacher.

Evaluation

Pro tutor (Qwen3.5 2B fine-tune, T-119), trained on the same data as the Light tutor. In the app, verdicts, corrections, word meanings and rule-card answers are written by the app itself; the model adds the conversation around them. Suggested only for high-end phones (≥11 GB RAM, ARMv8.6 CPU).

Files

  • laura-en-qwen3.5-2b-Q4_K_M.gguf — Q4_K_M, 1.27 GB

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