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ollama run julienp79/occitan-gemma-4-e2b-it-rslora-sfttrainer
Name
6 models
occitan-gemma-4-e2b-it-rslora-sfttrainer:latest
3.4GB · 128K context window · Text · yesterday
occitan-gemma-4-e2b-it-rslora-sfttrainer:Q2_K
3.0GB · 128K context window · Text · 2 days ago
occitan-gemma-4-e2b-it-rslora-sfttrainer:Q4_K_M
3.4GB · 128K context window · Text · 2 days ago
occitan-gemma-4-e2b-it-rslora-sfttrainer:Q5_K_M
3.6GB · 128K context window · Text · 2 days ago
occitan-gemma-4-e2b-it-rslora-sfttrainer:Q8_0
4.9GB · 128K context window · Text · 2 days ago
occitan-gemma-4-e2b-it-rslora-sfttrainer:f16
9.3GB · 128K context window · Text · 2 days ago
Fine-tune of Gemma 4 E2B Instruct on Occitan in the Lengadocian dialect (IEO grafia classica norm). Trained via QLoRA on literary, journalistic, grammar, and encyclopedic sources normalised to Lengadocian standard.
Best Gemma 4 model in the series. Holds three project records and delivers the richest literary vocabulary density of any model in the collection. Fast inference due to the 2B base.
Particularly strong on sustained literary prose with rare Lengadocian vocabulary (finòca, destriava, parpalhons negrós, roginassa, grols, lentèl, remòls, teulissas pesugadas, fogals petejats) and on dense journalistic register with zero interference.
Ès un escritor e grammarista occitan lengadocian. Respon unicament en
occitan lengadocian. Escriu dirèctament lo tèxte demandat, sens cap
d'introduccion, de comentari ni d'explicacion sus ton trabalh. Pas de
preamble. Pas de version multiplas. Pas de traduccion.
| Quant | Size | Use case |
|---|---|---|
| Q4_K_M | ~1.6 GB | Recommended — runs on any modern hardware |
| Q5_K_M | ~1.9 GB | Slightly better quality |
| Q8_0 | ~2.5 GB | Near-lossless |
| Q2_K | ~1.1 GB | Minimal RAM setups |
RS-LoRA · r=32 · α=32 · block_size=384 · 2535 steps · 5 epochs
RTX 3060 12GB · ~3h20m · FastVisionModel (text-only) + SFTTrainer