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md5("BE" (2 bytes) + 64-bit SteamID (8 bytes))

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public Program() {
    // The constructor, called only once every session and
    // always before any other method is called. Use it to
    // initialize your script. 
    //     
    // The constructor is optional and can be removed if not
    // needed.
}

public void Save() {

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# This file contains common pin mappings for the BIGTREETECH SKR mini
# E3 v2.0. To use this config, the firmware should be compiled for the
# STM32F103 with a "28KiB bootloader". Also, select "Enable extra
# low-level configuration options" and configure "GPIO pins to set at
# micro-controller startup" to "!PA14".

# The "make flash" command does not work on the SKR mini E3. Instead,
# after running "make", copy the generated "out/klipper.bin" file to a
# file named "firmware.bin" on an SD card and then restart the SKR
# mini E3 with that SD card.

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Card: AMD Instinct MI50 32 GB (gfx906 / Vega 20 / GCN5, ~1 TB/s HBM2, no matrix cores, passive-cooled) · replaced an Intel Arc B580 (permanent swap) Host: Nobara/Fedora, Ryzen 7 8845HS (8c/16t), 30 GB RAM · SELinux disabled · Docker Workload: n8n LLM node — "big data in → small data out" (prefill-dominated), single-user (--parallel 1) Compiled: 2026-07-03 — consolidates every test from 2026-06-20 → 2026-07-03. Source reports: MI50-report.md, MI50-MTP-speculative-decoding-analysis.md, MI50-Q5-Q6-quant-test.md, DFlash-setup.md, dflash-bench-2026-06-29.md, ornith-mtp-optimization-report.md, ornith-model-docker-logs-2026-07-01.md, llama-stats-2026-06-23.md, memory mi50-*.

Current production (2026-07-03): llama-hipgraphs container, image llama-hipgraphs:upstream-rocm-7.2.4 (build commit 0eca4d4, 2026-06-30), model Ornith-1.0-35B Q4_K_M + embedded MTP, --spec-type draft-mtp --spec-draft-n-max 2, 262 k ctx, q8_0 KV, --parallel 1, port 8089. ~70 t/s.

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#!/usr/bin/env python3
"""
Repro for vllm-project/vllm#48645 — deepseek_v4 parser: a reply that omits `</think>`
routes the entire answer to reasoning_content, leaving content empty (trailing EOS un-stripped).

Server must run (as the DeepSeek-V4-Flash recipe suggests):
  --reasoning-parser deepseek_v4 --tool-call-parser deepseek_v4 --enable-auto-tool-choice
  --default-chat-template-kwargs={"thinking":true,"reasoning_effort":"high"}

The request deliberately sends NO chat_template_kwargs — like any ordinary OpenAI-compatible