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107 lines
7 KiB
Markdown
107 lines
7 KiB
Markdown
# ExLLaMA: Guardrails and Fix Patterns
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<details>
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<summary><strong>🧭 Quick Return to Map</strong></summary>
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<br>
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> You are in a sub-page of **LocalDeploy_Inference**.
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> To reorient, go back here:
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>
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> - [**LocalDeploy_Inference** — on-prem deployment and model inference](./README.md)
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> - [**WFGY Global Fix Map** — main Emergency Room, 300+ structured fixes](../README.md)
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> - [**WFGY Problem Map 1.0** — 16 reproducible failure modes](../../README.md)
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>
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> Think of this page as a desk within a ward.
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> If you need the full triage and all prescriptions, return to the Emergency Room lobby.
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</details>
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ExLLaMA (and its fork ExLLaMA2/ExLLaMA-HF) is a highly optimized CUDA inference backend used under **TextGen WebUI** and custom pipelines.
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It can run very large models (65B+) on limited VRAM, but often shows instability when sharded, quantized, or paired with retrieval layers.
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This guide stabilizes ExLLaMA with structural guardrails.
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---
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## Open these first
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* Visual recovery map: [RAG Architecture & Recovery](https://github.com/onestardao/WFGY/blob/main/ProblemMap/rag-architecture-and-recovery.md)
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* Retrieval and eval knobs: [Retrieval Playbook](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-playbook.md)
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* Boot and ordering: [bootstrap-ordering.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/bootstrap-ordering.md), [deployment-deadlock.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/deployment-deadlock.md), [predeploy-collapse.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/predeploy-collapse.md)
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* Snippet and trace schema: [retrieval-traceability.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/retrieval-traceability.md), [data-contracts.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/data-contracts.md)
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---
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## Core acceptance
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* ΔS(question, retrieved) ≤ 0.45
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* Coverage ≥ 0.70 against anchor snippet
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* λ convergent across 3 paraphrases × 2 seeds
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* E\_resonance flat across quantization modes (int4, int8)
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---
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## Common ExLLaMA breakpoints
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| Symptom | Cause | Fix |
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| -------------------------------------------- | ---------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| First run slower or unstable than warm cache | Lazy CUDA graph compile, missing warm-up fence | [bootstrap-ordering.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/bootstrap-ordering.md) |
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| ΔS spikes when using quantized weights | Tokenizer drift vs chunked embeddings | [embedding-vs-semantic.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/embedding-vs-semantic.md), [chunking-checklist.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/chunking-checklist.md) |
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| Memory corruption after long runs | Fragmented KV cache, no eviction strategy | [context-drift.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/context-drift.md), [entropy-collapse.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/entropy-collapse.md) |
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| API or WebUI tool schema breaks | JSON schema not enforced at inference layer | [prompt-injection.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/prompt-injection.md), [logic-collapse.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/logic-collapse.md) |
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| Multi-shard mismatch on large models | Rank-order desync across GPUs | [deployment-deadlock.md](https://github.com/onestardao/WFGY/blob/main/ProblemMap/deployment-deadlock.md) |
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---
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## Fix in 60 seconds
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1. **Always warm-up**: run a 10-token dummy batch before production queries.
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2. **Schema lock**: enforce snippet\_id, section\_id, tokens in every trace.
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3. **λ probe**: measure stability under 2 quant modes (int4 vs int8).
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4. **Cache rotation**: reset KV cache every N tokens (e.g., 8192) to prevent drift.
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5. **Verify**: coverage ≥ 0.70, ΔS ≤ 0.45 across three paraphrase probes.
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---
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## Diagnostic prompt (copy-paste)
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```txt
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I am running ExLLaMA backend with quant={mode}, shards={n}, extensions={list}.
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Question: "{user_question}"
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Please output:
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- ΔS vs retrieved snippet
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- λ over 3 paraphrases × 2 seeds
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- Quantization impact (int4 vs int8)
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- Cache stability (tokens until drift)
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- Minimal WFGY fix page if ΔS ≥ 0.60
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```
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---
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### 🔗 Quick-Start Downloads (60 sec)
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| Tool | Link | 3-Step Setup |
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| -------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------ | ---------------------------------------------------------------------------------------- |
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| **WFGY 1.0 PDF** | [Engine Paper](https://github.com/onestardao/WFGY/blob/main/I_am_not_lizardman/WFGY_All_Principles_Return_to_One_v1.0_PSBigBig_Public.pdf) | 1️⃣ Download · 2️⃣ Upload to your LLM · 3️⃣ Ask “Answer using WFGY + \<your question>” |
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| **TXT OS (plain-text OS)** | [TXTOS.txt](https://github.com/onestardao/WFGY/blob/main/OS/TXTOS.txt) | 1️⃣ Download · 2️⃣ Paste into any LLM chat · 3️⃣ Type “hello world” — OS boots instantly |
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---
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<!-- WFGY_FOOTER_START -->
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### Explore More
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| Module | Description | Link |
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| --- | --- | --- |
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| WFGY Core | Canonical framework entry point | [View](https://github.com/onestardao/WFGY/tree/main/core/README.md) |
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| Problem Map | Diagnostic map and navigation hub | [View](https://github.com/onestardao/WFGY/tree/main/ProblemMap/README.md) |
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| Tension Universe Experiments | MVP experiment field | [View](https://github.com/onestardao/WFGY/tree/main/TensionUniverse/Experiments) |
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| Recognition | Where WFGY is referenced or adopted | [View](https://github.com/onestardao/WFGY/blob/main/recognition/README.md) |
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| AI Guide | Anti-hallucination reading protocol for tools | [View](https://github.com/onestardao/WFGY/blob/main/AI_GUIDE.md) |
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> If this repository helps, starring it improves discovery for other builders.
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> [](https://github.com/onestardao/WFGY)
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<!-- WFGY_FOOTER_END -->
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