Lucebox/Laguna-XS-2.1-DFlash-GGUF overview
Laguna XS 2.1 DFlash GGUF quantized drafter Quantized GGUF builds of the official poolside/Laguna XS 2.1 DFlash https://huggingface.co/poolside/Laguna XS 2.1 D…
Runs locally from ~258.9 MB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
Model Details
Model README
---
license: openmdw-1.1
base_model: poolside/Laguna-XS-2.1-DFlash
base_model_relation: quantized
tags:
- gguf
- dflash
- speculative-decoding
- laguna
- lucebox
---
Laguna-XS-2.1-DFlash-GGUF (quantized drafter)
Quantized GGUF builds of the official poolside/Laguna-XS-2.1-DFlash
speculator, packaged for the Lucebox inference engine's speculative decoding of
| file | scheme | size | notes |
|---|---|---|---|
| laguna-xs21-dflash-q4.gguf | Q4_0 projections, Q8_0 feature projection (fc), F32 norms | 271 MB | recommended |
| laguna-xs21-dflash-q8.gguf | Q8_0 projections, F32 norms | 492 MB | conservative |
Because speculative decoding verifies every draft against the target model,
drafter quantization cannot change the target's greedy output quality; the only
quantity at stake is acceptance length. Measured on an RTX 3090 with the
Laguna XS 2.1 Q4_K_M target (HumanEval/GSM8K/Math screens): acceptance
unchanged vs the BF16 drafter, end-to-end decode ~+3% (q4), gold-scored task
accuracy identical.
Produced with server/scripts/requant_dflash_draft.py from the lucebox engine
tree (GGUF-to-GGUF requant; all metadata, gates and aux norms preserved).
License: OpenMDW-1.1, inherited from the base speculator. All credit for the
DFlash speculator weights to poolside.
Run Lucebox/Laguna-XS-2.1-DFlash-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models