Request board: how to request a quant or abliteration

README.md

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+---
+license: apache-2.0
+tags:
+- requests
+- gguf
+- abliterated
+- reap
+- quantization
+---
+
+# Request a quant or abliteration
+
+Robinson Labs forges open models on a real homelab cluster: abliterated builds, REAP expert-pruned
+MoE variants, importance-matrix (imatrix) GGUF quant ladders, and custom cluster-fit quants. This
+repo is where you ask for one.
+
+See what we have published: [huggingface.co/RobinsonLabs](https://huggingface.co/RobinsonLabs).
+
+## How to request
+Open a new **Discussion** (the **Community** tab at the top of this repo) with:
+- A link to the model on Hugging Face (the original or base repo).
+- What you want: a GGUF quant ladder, an abliterated build, a REAP-pruned variant, or a fit-quant
+  tuned to a specific VRAM and context budget.
+- Your target, if you have one: VRAM size, context length, or a specific quant (for example IQ4_XS,
+  Q6_K).
+
+One model per Discussion keeps things easy to track.
+
+## What we prioritize
+We are a one-person homelab, not a quant farm, so we bias toward the gaps, the builds that do not
+already exist:
+- **Abliterated builds** where there is no good uncensored variant yet.
+- **Abliterated REAP / expert-pruned MoE**, a niche almost nobody fills.
+- **Custom cluster-fit quants** tuned to a real VRAM and context budget (attention-path precision
+  kept high where it counts, experts run lighter).
+- Models that lack a solid imatrix GGUF ladder.
+
+If a model already has good quants from the usual sources, we will likely point you there. Where we
+add value is the build that is missing.
+
+## What to expect
+Best-effort, on hardware we own. No SLA, no queue promises. Every release ships with full provenance
+and credits the upstream base author. On abliterated builds, harm guardrails stay intact by design
+(self-harm prompts still redirect to help, and the build is not meant to assist genuine wrongdoing).
+
+You are responsible for your use of any model published here.