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Model: Cyb3RQ/arabic-poetry-qwen3-8b-GGUF
Source: Original Platform

README.md

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+---
+license: apache-2.0
+language:
+- ar
+base_model: unsloth/Qwen3-8B
+tags:
+- arabic
+- poetry
+- qwen3
+- gguf
+- lora
+- experimental
+pipeline_tag: text-generation
+---
+
+# Arabic Poetry Qwen3-8B (LoRA, GGUF) — Experimental
+
+> **Status: experimental / hobby project.** This model produces *coherent
+> Arabic in a loose poetic register*. It does **not** reliably produce correct
+> classical meter (بحر) or rhyme (قافية), and output quality is uneven. Set
+> expectations accordingly. Read the Limitations section before using.
+
+A LoRA fine-tune of **Qwen3-8B** on a corpus of Arabic poetry that was OCR'd
+locally from 19 books. Trained as continued-pretraining on discrete poems.
+
+## What it actually does
+
+- Generates Arabic text with a poem-like shape (short lines, stops cleanly)
+- Stays in Arabic, on the prompt's theme more than the base model does
+- Style leans modern/free-verse (Darwish-ish), not classical ode
+
+## What it does NOT do well
+
+- **No reliable meter or rhyme.** It does not scan to a specific بحر.
+- Imagery is often weak or vague; some lines are semantically loose.
+- Quality varies a lot run-to-run.
+- Classical/Jahiliyya register is weak (the OCR corpus had artifacts).
+
+This is a **data-and-scale-limited** result: ~2,244 OCR'd poems (with residual
+OCR noise) on an 8B model is not enough to install genuine Arabic prosody. It
+is shared as an experiment and a starting point, not a finished poetry engine.
+
+## Usage (LM Studio / llama.cpp)
+
+Download `arabic-poetry-qwen3-8b-f16.gguf`. Recommended sampling:
+
+- Temperature `0.7`, Top-p `0.92`, Top-k `40`
+- **Repeat penalty `1.3`** (lower values loop)
+- Reasoning/thinking: **OFF**
+- System prompt: empty
+
+Prompt with Arabic openers, not English instructions:
+
+```
+قصيدة في وصف الصحراء:
+في حضرة الغياب،
+أحبكِ يا وطني،
+```
+
+> Note: send prompts via a UTF-8-correct client. Some terminal/curl setups on
+> Windows mangle Arabic UTF-8 and will make the model emit garbage — that is a
+> client encoding bug, not the model.
+
+## Training
+
+| | |
+|---|---|
+| Base | `unsloth/Qwen3-8B` (full bf16, not quantized) |
+| Method | LoRA r=32 α=32, attention-only, dropout 0.05 |
+| Data | 2,244 discrete cleaned Arabic poems, EOS-terminated |
+| Schedule | 2 epochs, cosine LR 1.2e-4, manual training loop |
+| Selection | best pre-overfit checkpoint by sample quality (not final) |
+| Hardware | single RTX 4090, ~19 min |
+
+## License
+
+Apache-2.0 (inherits from Qwen3-8B).
+
+## Honest note
+
+Built end-to-end on a single workstation (OCR → corpus cleaning → LoRA → GGUF).
+The most reusable artifact from the project is arguably the cleaned corpus and
+pipeline, not this particular adapter. Contributions / a cleaner meter-labelled
+Arabic corpus would meaningfully improve a v2.