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esh-pfi-infrastructure/servers/ana-ml2/system-details.txt
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vh 355a2407a2 docs(ana-ml2): correct GPU spec Ada -> RTX PRO 6000 Blackwell (96GB, cc 12.0) 
ana-ml2 was upgraded 2026-06 from dual RTX 6000 Ada (46GB, cc 8.9) to
dual RTX PRO 6000 Blackwell Max-Q (96GB, cc 12.0 / sm_120). Update the
stale hardware facts across the workspace:

- CLAUDE.md servers table row
- servers/ana-ml2/README.md hardware spec (+ refreshed system-details.txt)
- stacks/vllm compose + .env.example FP8/KV comments (Ada cc 8.9 -> Blackwell cc 12.0)
- stacks/llama-swap config VRAM-budget comment (48GB -> 96GB, GPU-0 pin)

Also corrects the adjacent stale 'Phi-4-mini' comment in the granite
service block (the service has been Granite 4.1 8B since 34a43a0).
Doc/comment-only; no runtime change.
2026-06-13 13:36:14 -07:00

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===== HOST =====
Hostname: ana-ml2
Date: 2026-06-13T13:35:42-07:00
Uptime: up 1 day, 6 minutes
OS: Debian GNU/Linux 13 (trixie)
Kernel: 6.12.74+deb13+1-amd64
Arch: x86_64
===== HARDWARE =====
CPU cores: 96
CPU model: AMD EPYC 9254 24-Core Processor
MemTotal: 566.6 GB
MemAvailable: 484.5 GB
===== GPUS =====
index, name, memory.total [MiB], memory.free [MiB], driver_version
0, NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition, 97887 MiB, 97247 MiB, 580.65.06
1, NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition, 97887 MiB, 3692 MiB, 580.65.06
===== FILESYSTEMS (df) =====
Filesystem Size Used Avail Use% Mounted on
zroot/ROOT/debian 394G 212G 182G 54% /
efivarfs 128K 67K 57K 55% /sys/firmware/efi/efivars
/dev/sdb1 511M 92M 420M 18% /boot/efi
tank 8.6T 1.6T 7.1T 18% /tank
zroot/home 244G 62G 182G 26% /home
===== PERSISTENT MOUNTS (/etc/fstab, non-comment) =====
UUID="3D9B-8E0C" /boot/efi vfat defaults 0 0
===== TARGETED DATA PATHS =====
/tank (total: 1.6T)
total 15
drwxrwxrwx 6 root root 6 2026-04-11 23:17 .
drwxr-xr-x 18 root root 26 2026-03-29 16:08 ..
drwxrwxr-x 9 llmuser llm 10 2026-06-12 18:01 aimodels
drwxrwxr-x 3 llmuser llm 3 2025-09-08 13:21 comfy
drwxrwxr-x 4 llmuser llmuser 4 2026-04-11 23:17 kokoro
drwxrwxr-x 5 lkraven lkraven 6 2025-09-10 18:35 vibevoice
/opt (total: 16G)
total 79
drwxrwxrwx 13 root root 13 2026-04-17 23:00 .
drwxr-xr-x 18 root root 26 2026-03-29 16:08 ..
drwx--x--x 4 root root 4 2025-09-02 12:53 containerd
drwxrwxr-x 4 lkraven lkraven 4 2025-09-03 20:19 docker
drwxrwxr-x 8 llmuser llm 17 2026-04-17 17:50 heretic
drwxrwxr-x 15 llmuser llmuser 36 2026-04-11 23:24 Kokoro-FastAPI
drwxrwxr-x 20 llmuser llmuser 39 2025-10-09 21:42 LibreChat
drwxrwxr-x 26 llmuser llmuser 56 2025-09-04 21:01 llama.cpp
drwxrwxr-x 13 llmuser llmuser 25 2025-09-02 12:50 llama-swap
drwxrwxr-x 3 llmuser llmuser 11 2026-04-18 15:48 llmcompressor
drwxr-xr-x 4 root root 4 2025-08-30 22:54 nvidia
drwxrwxr-x 6 llmuser llmuser 15 2025-09-24 09:53 parakeet-tdt-0.6b-v2-fastapi
drwxrwxr-x 2 llmuser llmuser 6 2025-09-05 10:03 uv
/opt/docker (total: 110M)
total 18
drwxrwxr-x 4 lkraven lkraven 4 2025-09-03 20:19 .
drwxrwxrwx 13 root root 13 2026-04-17 23:00 ..
drwxrwxr-x 12 lkraven lkraven 12 2026-06-13 02:32 compose
drwxrwxr-x 4 lkraven lkraven 4 2026-06-04 00:26 conf
/opt/docker/compose (total: 110M)
total 30
drwxrwxr-x 12 lkraven lkraven 12 2026-06-13 02:32 .
drwxrwxr-x 4 lkraven lkraven 4 2025-09-03 20:19 ..
drwxr-xr-x 2 lkraven lkraven 4 2026-04-20 18:47 beszel-agent-ana
drwxr-xr-x 2 lkraven lkraven 4 2025-09-05 20:36 comfyui
drwxr-xr-x 2 lkraven lkraven 4 2026-04-20 20:47 dockge
drwxr-xr-x 2 lkraven lkraven 4 2026-04-20 20:44 dozzle-agent-ana
drwxrwxr-x 3 lkraven lkraven 4 2026-04-11 23:17 kokoro
drwxr-xr-x 2 lkraven lkraven 6 2026-06-12 15:17 llama-swap
drwxr-xr-x 2 lkraven lkraven 4 2025-09-24 12:32 parakeet
drwxrwxr-x 2 lkraven lkraven 4 2026-06-13 08:34 qwen35-vl
drwxr-xr-x 2 lkraven lkraven 4 2025-09-10 18:03 vibevoice
drwxr-xr-x 2 lkraven lkraven 9 2026-06-13 08:42 vllm
/opt/docker/conf (total: 14K)
total 2
drwxrwxr-x 4 lkraven lkraven 4 2026-06-04 00:26 .
drwxrwxr-x 4 lkraven lkraven 4 2025-09-03 20:19 ..
drwxr-xr-x 2 lkraven lkraven 3 2026-06-05 00:22 llama-swap
drwxr-xr-x 2 lkraven lkraven 2 2026-06-04 00:37 vllm
/var/lib/docker (total: 8.5K)
/srv (total: 512)
total 9
drwxr-xr-x 2 root root 2 2025-08-30 18:46 .
drwxr-xr-x 18 root root 26 2026-03-29 16:08 ..
===== DOCKER =====
Server: 29.3.1 Client: 29.3.1
----- docker info -----
Containers: 9 (running 9, paused 0, stopped 0)
Images: 42
Runtimes: map[io.containerd.runc.v2:{{runc [] map[]} map[org.opencontainers.runtime-spec.features:{"ociVersionMin":"1.0.0","ociVersionMax":"1.2.1","hooks":["prestart","createRuntime","createContainer","startContainer","poststart","poststop"],"mountOptions":["async","atime","bind","defaults","dev","diratime","dirsync","exec","iversion","lazytime","loud","mand","noatime","nodev","nodiratime","noexec","noiversion","nolazytime","nomand","norelatime","nostrictatime","nosuid","nosymfollow","private","ratime","rbind","rdev","rdiratime","relatime","remount","rexec","rnoatime","rnodev","rnodiratime","rnoexec","rnorelatime","rnostrictatime","rnosuid","rnosymfollow","ro","rprivate","rrelatime","rro","rrw","rshared","rslave","rstrictatime","rsuid","rsymfollow","runbindable","rw","shared","silent","slave","strictatime","suid","symfollow","sync","tmpcopyup","unbindable"],"linux":{"namespaces":["cgroup","ipc","mount","network","pid","time","user","uts"],"capabilities":["CAP_CHOWN","CAP_DAC_OVERRIDE","CAP_DAC_READ_SEARCH","CAP_FOWNER","CAP_FSETID","CAP_KILL","CAP_SETGID","CAP_SETUID","CAP_SETPCAP","CAP_LINUX_IMMUTABLE","CAP_NET_BIND_SERVICE","CAP_NET_BROADCAST","CAP_NET_ADMIN","CAP_NET_RAW","CAP_IPC_LOCK","CAP_IPC_OWNER","CAP_SYS_MODULE","CAP_SYS_RAWIO","CAP_SYS_CHROOT","CAP_SYS_PTRACE","CAP_SYS_PACCT","CAP_SYS_ADMIN","CAP_SYS_BOOT","CAP_SYS_NICE","CAP_SYS_RESOURCE","CAP_SYS_TIME","CAP_SYS_TTY_CONFIG","CAP_MKNOD","CAP_LEASE","CAP_AUDIT_WRITE","CAP_AUDIT_CONTROL","CAP_SETFCAP","CAP_MAC_OVERRIDE","CAP_MAC_ADMIN","CAP_SYSLOG","CAP_WAKE_ALARM","CAP_BLOCK_SUSPEND","CAP_AUDIT_READ","CAP_PERFMON","CAP_BPF","CAP_CHECKPOINT_RESTORE"],"cgroup":{"v1":true,"v2":true,"systemd":true,"systemdUser":true,"rdma":true},"seccomp":{"enabled":true,"actions":["SCMP_ACT_ALLOW","SCMP_ACT_ERRNO","SCMP_ACT_KILL","SCMP_ACT_KILL_PROCESS","SCMP_ACT_KILL_THREAD","SCMP_ACT_LOG","SCMP_ACT_NOTIFY","SCMP_ACT_TRACE","SCMP_ACT_TRAP"],"operators":["SCMP_CMP_EQ","SCMP_CMP_GE","SCMP_CMP_GT","SCMP_CMP_LE","SCMP_CMP_LT","SCMP_CMP_MASKED_EQ","SCMP_CMP_NE"],"archs":["SCMP_ARCH_AARCH64","SCMP_ARCH_ARM","SCMP_ARCH_MIPS","SCMP_ARCH_MIPS64","SCMP_ARCH_MIPS64N32","SCMP_ARCH_MIPSEL","SCMP_ARCH_MIPSEL64","SCMP_ARCH_MIPSEL64N32","SCMP_ARCH_PPC","SCMP_ARCH_PPC64","SCMP_ARCH_PPC64LE","SCMP_ARCH_RISCV64","SCMP_ARCH_S390","SCMP_ARCH_S390X","SCMP_ARCH_X32","SCMP_ARCH_X86","SCMP_ARCH_X86_64"],"knownFlags":["SECCOMP_FILTER_FLAG_TSYNC","SECCOMP_FILTER_FLAG_SPEC_ALLOW","SECCOMP_FILTER_FLAG_LOG"],"supportedFlags":["SECCOMP_FILTER_FLAG_TSYNC","SECCOMP_FILTER_FLAG_SPEC_ALLOW","SECCOMP_FILTER_FLAG_LOG"]},"apparmor":{"enabled":true},"selinux":{"enabled":true},"intelRdt":{"enabled":true},"mountExtensions":{"idmap":{"enabled":true}}},"annotations":{"io.github.seccomp.libseccomp.version":"2.6.0","org.opencontainers.runc.checkpoint.enabled":"true","org.opencontainers.runc.commit":"v1.3.4-0-gd6d73eb8","org.opencontainers.runc.version":"1.3.4\n"},"potentiallyUnsafeConfigAnnotations":["bundle","org.systemd.property.","org.criu.config"]}]} nvidia:{{nvidia-container-runtime [] map[]} map[org.opencontainers.runtime-spec.features:{"ociVersionMin":"1.0.0","ociVersionMax":"1.2.1","hooks":["prestart","createRuntime","createContainer","startContainer","poststart","poststop"],"mountOptions":["async","atime","bind","defaults","dev","diratime","dirsync","exec","iversion","lazytime","loud","mand","noatime","nodev","nodiratime","noexec","noiversion","nolazytime","nomand","norelatime","nostrictatime","nosuid","nosymfollow","private","ratime","rbind","rdev","rdiratime","relatime","remount","rexec","rnoatime","rnodev","rnodiratime","rnoexec","rnorelatime","rnostrictatime","rnosuid","rnosymfollow","ro","rprivate","rrelatime","rro","rrw","rshared","rslave","rstrictatime","rsuid","rsymfollow","runbindable","rw","shared","silent","slave","strictatime","suid","symfollow","sync","tmpcopyup","unbindable"],"linux":{"namespaces":["cgroup","ipc","mount","network","pid","time","user","uts"],"capabilities":["CAP_CHOWN","CAP_DAC_OVERRIDE","CAP_DAC_READ_SEARCH","CAP_FOWNER","CAP_FSETID","CAP_KILL","CAP_SETGID","CAP_SETUID","CAP_SETPCAP","CAP_LINUX_IMMUTABLE","CAP_NET_BIND_SERVICE","CAP_NET_BROADCAST","CAP_NET_ADMIN","CAP_NET_RAW","CAP_IPC_LOCK","CAP_IPC_OWNER","CAP_SYS_MODULE","CAP_SYS_RAWIO","CAP_SYS_CHROOT","CAP_SYS_PTRACE","CAP_SYS_PACCT","CAP_SYS_ADMIN","CAP_SYS_BOOT","CAP_SYS_NICE","CAP_SYS_RESOURCE","CAP_SYS_TIME","CAP_SYS_TTY_CONFIG","CAP_MKNOD","CAP_LEASE","CAP_AUDIT_WRITE","CAP_AUDIT_CONTROL","CAP_SETFCAP","CAP_MAC_OVERRIDE","CAP_MAC_ADMIN","CAP_SYSLOG","CAP_WAKE_ALARM","CAP_BLOCK_SUSPEND","CAP_AUDIT_READ","CAP_PERFMON","CAP_BPF","CAP_CHECKPOINT_RESTORE"],"cgroup":{"v1":true,"v2":true,"systemd":true,"systemdUser":true,"rdma":true},"seccomp":{"enabled":true,"actions":["SCMP_ACT_ALLOW","SCMP_ACT_ERRNO","SCMP_ACT_KILL","SCMP_ACT_KILL_PROCESS","SCMP_ACT_KILL_THREAD","SCMP_ACT_LOG","SCMP_ACT_NOTIFY","SCMP_ACT_TRACE","SCMP_ACT_TRAP"],"operators":["SCMP_CMP_EQ","SCMP_CMP_GE","SCMP_CMP_GT","SCMP_CMP_LE","SCMP_CMP_LT","SCMP_CMP_MASKED_EQ","SCMP_CMP_NE"],"archs":["SCMP_ARCH_AARCH64","SCMP_ARCH_ARM","SCMP_ARCH_MIPS","SCMP_ARCH_MIPS64","SCMP_ARCH_MIPS64N32","SCMP_ARCH_MIPSEL","SCMP_ARCH_MIPSEL64","SCMP_ARCH_MIPSEL64N32","SCMP_ARCH_PPC","SCMP_ARCH_PPC64","SCMP_ARCH_PPC64LE","SCMP_ARCH_RISCV64","SCMP_ARCH_S390","SCMP_ARCH_S390X","SCMP_ARCH_X32","SCMP_ARCH_X86","SCMP_ARCH_X86_64"],"knownFlags":["SECCOMP_FILTER_FLAG_TSYNC","SECCOMP_FILTER_FLAG_SPEC_ALLOW","SECCOMP_FILTER_FLAG_LOG"],"supportedFlags":["SECCOMP_FILTER_FLAG_TSYNC","SECCOMP_FILTER_FLAG_SPEC_ALLOW","SECCOMP_FILTER_FLAG_LOG"]},"apparmor":{"enabled":true},"selinux":{"enabled":true},"intelRdt":{"enabled":true},"mountExtensions":{"idmap":{"enabled":true}}},"annotations":{"io.github.seccomp.libseccomp.version":"2.6.0","org.opencontainers.runc.checkpoint.enabled":"true","org.opencontainers.runc.commit":"v1.3.4-0-gd6d73eb8","org.opencontainers.runc.version":"1.3.4\n"},"potentiallyUnsafeConfigAnnotations":["bundle","org.systemd.property.","org.criu.config"]}]} runc:{{runc [] map[]} map[org.opencontainers.runtime-spec.features:{"ociVersionMin":"1.0.0","ociVersionMax":"1.2.1","hooks":["prestart","createRuntime","createContainer","startContainer","poststart","poststop"],"mountOptions":["async","atime","bind","defaults","dev","diratime","dirsync","exec","iversion","lazytime","loud","mand","noatime","nodev","nodiratime","noexec","noiversion","nolazytime","nomand","norelatime","nostrictatime","nosuid","nosymfollow","private","ratime","rbind","rdev","rdiratime","relatime","remount","rexec","rnoatime","rnodev","rnodiratime","rnoexec","rnorelatime","rnostrictatime","rnosuid","rnosymfollow","ro","rprivate","rrelatime","rro","rrw","rshared","rslave","rstrictatime","rsuid","rsymfollow","runbindable","rw","shared","silent","slave","strictatime","suid","symfollow","sync","tmpcopyup","unbindable"],"linux":{"namespaces":["cgroup","ipc","mount","network","pid","time","user","uts"],"capabilities":["CAP_CHOWN","CAP_DAC_OVERRIDE","CAP_DAC_READ_SEARCH","CAP_FOWNER","CAP_FSETID","CAP_KILL","CAP_SETGID","CAP_SETUID","CAP_SETPCAP","CAP_LINUX_IMMUTABLE","CAP_NET_BIND_SERVICE","CAP_NET_BROADCAST","CAP_NET_ADMIN","CAP_NET_RAW","CAP_IPC_LOCK","CAP_IPC_OWNER","CAP_SYS_MODULE","CAP_SYS_RAWIO","CAP_SYS_CHROOT","CAP_SYS_PTRACE","CAP_SYS_PACCT","CAP_SYS_ADMIN","CAP_SYS_BOOT","CAP_SYS_NICE","CAP_SYS_RESOURCE","CAP_SYS_TIME","CAP_SYS_TTY_CONFIG","CAP_MKNOD","CAP_LEASE","CAP_AUDIT_WRITE","CAP_AUDIT_CONTROL","CAP_SETFCAP","CAP_MAC_OVERRIDE","CAP_MAC_ADMIN","CAP_SYSLOG","CAP_WAKE_ALARM","CAP_BLOCK_SUSPEND","CAP_AUDIT_READ","CAP_PERFMON","CAP_BPF","CAP_CHECKPOINT_RESTORE"],"cgroup":{"v1":true,"v2":true,"systemd":true,"systemdUser":true,"rdma":true},"seccomp":{"enabled":true,"actions":["SCMP_ACT_ALLOW","SCMP_ACT_ERRNO","SCMP_ACT_KILL","SCMP_ACT_KILL_PROCESS","SCMP_ACT_KILL_THREAD","SCMP_ACT_LOG","SCMP_ACT_NOTIFY","SCMP_ACT_TRACE","SCMP_ACT_TRAP"],"operators":["SCMP_CMP_EQ","SCMP_CMP_GE","SCMP_CMP_GT","SCMP_CMP_LE","SCMP_CMP_LT","SCMP_CMP_MASKED_EQ","SCMP_CMP_NE"],"archs":["SCMP_ARCH_AARCH64","SCMP_ARCH_ARM","SCMP_ARCH_MIPS","SCMP_ARCH_MIPS64","SCMP_ARCH_MIPS64N32","SCMP_ARCH_MIPSEL","SCMP_ARCH_MIPSEL64","SCMP_ARCH_MIPSEL64N32","SCMP_ARCH_PPC","SCMP_ARCH_PPC64","SCMP_ARCH_PPC64LE","SCMP_ARCH_RISCV64","SCMP_ARCH_S390","SCMP_ARCH_S390X","SCMP_ARCH_X32","SCMP_ARCH_X86","SCMP_ARCH_X86_64"],"knownFlags":["SECCOMP_FILTER_FLAG_TSYNC","SECCOMP_FILTER_FLAG_SPEC_ALLOW","SECCOMP_FILTER_FLAG_LOG"],"supportedFlags":["SECCOMP_FILTER_FLAG_TSYNC","SECCOMP_FILTER_FLAG_SPEC_ALLOW","SECCOMP_FILTER_FLAG_LOG"]},"apparmor":{"enabled":true},"selinux":{"enabled":true},"intelRdt":{"enabled":true},"mountExtensions":{"idmap":{"enabled":true}}},"annotations":{"io.github.seccomp.libseccomp.version":"2.6.0","org.opencontainers.runc.checkpoint.enabled":"true","org.opencontainers.runc.commit":"v1.3.4-0-gd6d73eb8","org.opencontainers.runc.version":"1.3.4\n"},"potentiallyUnsafeConfigAnnotations":["bundle","org.systemd.property.","org.criu.config"]}]}]
Default runtime: runc
Storage driver: overlay2
Root dir: /var/lib/docker
Server version: 29.3.1
----- running containers -----
NAMES IMAGE STATUS PORTS
vllm-qwen35 vllm/vllm-openai Up About an hour (healthy) 0.0.0.0:8007->8000/tcp, [::]:8007->8000/tcp
vllm-granite vllm/vllm-openai:latest Up About an hour (healthy) 0.0.0.0:8004->8000/tcp, [::]:8004->8000/tcp
vllm-rerank vllm/vllm-openai:latest Up 13 hours (healthy) 0.0.0.0:8002->8000/tcp, [::]:8002->8000/tcp
vllm-embed vllm/vllm-openai:latest Up 13 hours (healthy) 0.0.0.0:8001->8000/tcp, [::]:8001->8000/tcp
vllm-reward vllm/vllm-openai:latest Up 13 hours (healthy) 0.0.0.0:8003->8000/tcp, [::]:8003->8000/tcp
llama-swap ghcr.io/mostlygeek/llama-swap:cuda Up 13 hours (healthy) 0.0.0.0:9292->8080/tcp, [::]:9292->8080/tcp
dockge louislam/dockge:latest Up 13 hours (healthy) 0.0.0.0:5001->5001/tcp, [::]:5001->5001/tcp
dozzle-agent amir20/dozzle:latest Up 13 hours 0.0.0.0:7007->7007/tcp, 8080/tcp
beszel-agent henrygd/beszel-agent:latest Up 13 hours (healthy)
----- all containers -----
NAMES IMAGE STATUS
vllm-qwen35 vllm/vllm-openai Up About an hour (healthy)
vllm-granite vllm/vllm-openai:latest Up About an hour (healthy)
vllm-rerank vllm/vllm-openai:latest Up 13 hours (healthy)
vllm-embed vllm/vllm-openai:latest Up 13 hours (healthy)
vllm-reward vllm/vllm-openai:latest Up 13 hours (healthy)
llama-swap ghcr.io/mostlygeek/llama-swap:cuda Up 13 hours (healthy)
dockge louislam/dockge:latest Up 13 hours (healthy)
dozzle-agent amir20/dozzle:latest Up 13 hours
beszel-agent henrygd/beszel-agent:latest Up 13 hours (healthy)
----- networks -----
NAME DRIVER SCOPE
bridge bridge local
host host local
kokoro-tts-gpu_default bridge local
librechat_default bridge local
llama-swap_default bridge local
none null local
traefik-net bridge local
----- networks (external, non-default — worth knowing for compose external: true) -----
kokoro-tts-gpu_default
librechat_default
llama-swap_default
traefik-net
----- named volumes -----
VOLUME NAME DRIVER
beszel-agent-ana_beszel_agent_data local
dockge_dockge_data local
dozzle-agent-ana_dozzle_agent_data local
parakeet_parakeet_cache local
searxng_searxng-data local
----- compose projects currently running -----
beszel-agent-ana
dockge
dozzle-agent-ana
llama-swap
qwen35-vl
vllm
===== COMPOSE FILES (/opt/docker/compose/) =====
>>> /opt/docker/compose/beszel-agent-ana/compose.yaml
# Beszel — lightweight server/container monitoring.
#
# Hub: single web UI with the SQLite store. Agents: per-host metric collectors
# that the hub pulls from over SSH.
#
# Multi-host layout via compose profiles:
# COMPOSE_PROFILES=hub → hub only (ana-docker)
# COMPOSE_PROFILES=hub,agent → hub + local agent on the same host
# COMPOSE_PROFILES=agent → agent only (ana-ml2, nh3-docker,
# esh-docker-vm, vm-esh-nas)
#
# The agent uses network_mode: host so it sees real host CPU/mem/net/disk
# counters rather than container-scoped ones — that's why it can't share
# the tnet network with the hub.
#
# All tunables live in .env — edit that, not this file.
services:
beszel:
image: henrygd/beszel:${BESZEL_VERSION}
container_name: beszel
profiles: [hub]
restart: unless-stopped
ports:
- "${BESZEL_PORT}:8090"
volumes:
- beszel_data:/beszel_data
healthcheck:
# Hub image is distroless — no wget/curl. Use the bundled `/beszel`
# binary's built-in health subcommand (https://beszel.dev/guide/healthchecks).
test: ["CMD", "/beszel", "health", "--url", "http://localhost:8090"]
interval: 120s
timeout: 10s
retries: 3
start_period: 15s
networks:
- tnet
labels:
- homepage.group=Monitoring
- homepage.name=Beszel
- homepage.icon=mdi-chart-line
- homepage.description=Server + container monitoring
- homepage.href=http://10.250.50.70:${BESZEL_PORT}
beszel-agent:
image: henrygd/beszel-agent:${BESZEL_VERSION}
container_name: beszel-agent
profiles: [agent]
restart: unless-stopped
network_mode: host
volumes:
- /var/run/docker.sock:/var/run/docker.sock:ro
- beszel_agent_data:/var/lib/beszel-agent
environment:
# Agent auth has two modes (v0.13+ supports both side-by-side):
# - KEY-mode: agent listens, hub connects inbound over SSH using KEY.
# Requires BESZEL_HUB_KEY in .env.
# - Token-mode: agent initiates an outbound connection to HUB_URL
# using TOKEN. Easier through NAT. Requires HUB_URL + BESZEL_TOKEN.
# Leave unused ones empty ("") in .env; both can be set simultaneously.
- PORT=${BESZEL_AGENT_PORT:-45876}
- KEY=${BESZEL_HUB_KEY:-}
- HUB_URL=${HUB_URL:-}
- TOKEN=${BESZEL_TOKEN:-}
- EXTRA_FILESYSTEMS=${BESZEL_EXTRA_FS:-}
healthcheck:
# Agent image ships the `/agent` binary with a `health` subcommand.
# Verifies the agent process is up — not that the hub can reach it.
test: ["CMD", "/agent", "health"]
interval: 120s
timeout: 10s
retries: 3
start_period: 15s
volumes:
beszel_data:
beszel_agent_data:
networks:
tnet:
name: traefik-net
external: true
>>> /opt/docker/compose/comfyui/compose.yaml
services:
comfyui:
runtime: nvidia
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: all
capabilities:
- gpu
- compute
- utility
ports:
- 8188:8188
image: mmartial/comfyui-nvidia-docker:ubuntu24_cuda13.0-latest
networks:
- tnet
volumes:
- /tank/comfy/run:/comfy/mnt
- /tank/aimodels/img/comfy:/basedir
#user: 1001:1002
environment:
- WANTED_UID=1001
- WANTED_GID=1002
- BASE_DIRECTORY=/basedir
- SECURITY_LEVEL=weak
- NVIDIA_VISIBLE_DEVICES=all
- NVIDIA_DRIVER_CAPABILITIES=all
labels:
- homepage.group=AI Systems
- homepage.name=ComfyUI
- homepage.icon=mdi-panorama-variant-outline
- homepage.description=ComfyUI Image Gen (ana-ml2)
- homepage.href=http://10.250.50.54:8188
restart: unless-stopped
networks:
tnet:
name: traefik-net
external: true
>>> /opt/docker/compose/dockge/compose.yaml
# Dockge — per-host Docker Compose UI (https://dockge.kuma.pet/).
#
# One instance runs on every Docker host so the compose dir is manageable
# from a browser. Each host sets DOCKGE_HOST_LABEL + DOCKGE_HOST_IP in its
# .env so the homepage card points at the right place.
#
# All tunables live in .env — edit that, not this file.
services:
dockge:
image: louislam/dockge:${DOCKGE_VERSION:-latest}
container_name: dockge
restart: unless-stopped
ports:
- "${DOCKGE_PORT:-5001}:5001"
volumes:
- /var/run/docker.sock:/var/run/docker.sock
- dockge_data:/app/data
- /opt/docker:/opt/docker
environment:
- DOCKGE_STACKS_DIR=/opt/docker/compose
networks:
- tnet
labels:
- homepage.group=Service Networking
- homepage.name=Dockge (${DOCKGE_HOST_LABEL})
- homepage.icon=sh-dockge.png
- homepage.description=Compose UI on ${DOCKGE_HOST_LABEL}
- homepage.href=http://${DOCKGE_HOST_IP}:${DOCKGE_PORT:-5001}
volumes:
dockge_data:
networks:
tnet:
name: traefik-net
external: true
>>> /opt/docker/compose/dozzle-agent-ana/compose.yaml
# Dozzle — container log viewer.
#
# Multi-host layout via compose profiles:
# COMPOSE_PROFILES=hub → runs the web UI (deploy on ana-docker)
# COMPOSE_PROFILES=agent → runs the remote agent (deploy on ana-ml2)
#
# Same compose.yaml on both servers; per-host `.env` picks the profile.
#
# All tunables live in .env — edit that, not this file.
services:
dozzle:
image: amir20/dozzle:${DOZZLE_VERSION}
container_name: dozzle
profiles: [hub]
restart: unless-stopped
ports:
- "${DOZZLE_PORT}:8080"
volumes:
- /var/run/docker.sock:/var/run/docker.sock:ro
- dozzle_data:/data
environment:
- DOZZLE_HOSTNAME=${DOZZLE_HOSTNAME}
- DOZZLE_REMOTE_AGENT=${DOZZLE_REMOTE_AGENT:-}
- DOZZLE_AUTH_PROVIDER=${DOZZLE_AUTH_PROVIDER:-none}
- DOZZLE_USERNAME=${DOZZLE_USERNAME:-}
- DOZZLE_PASSWORD=${DOZZLE_PASSWORD:-}
healthcheck:
test: ["CMD", "/dozzle", "healthcheck"]
interval: 30s
timeout: 10s
retries: 3
start_period: 15s
networks:
- tnet
labels:
- homepage.group=Monitoring
- homepage.name=Dozzle
- homepage.icon=mdi-text-box-search
- homepage.description=Container logs (ana-docker + ana-ml2)
- homepage.href=http://10.250.50.70:${DOZZLE_PORT}
dozzle-agent:
image: amir20/dozzle:${DOZZLE_VERSION}
container_name: dozzle-agent
profiles: [agent]
restart: unless-stopped
command: agent
ports:
- "${DOZZLE_AGENT_BIND:-0.0.0.0}:${DOZZLE_AGENT_PORT}:7007"
volumes:
- /var/run/docker.sock:/var/run/docker.sock:ro
- dozzle_agent_data:/data
environment:
- DOZZLE_HOSTNAME=${DOZZLE_HOSTNAME}
networks:
- tnet
volumes:
dozzle_data:
dozzle_agent_data:
networks:
tnet:
name: traefik-net
external: true
>>> /opt/docker/compose/kokoro/compose.yaml
name: kokoro-tts
services:
kokoro-tts:
container_name: kokoro-tts
build:
context: ./Kokoro-FastAPI
dockerfile: docker/gpu/Dockerfile
volumes:
- /tank/kokoro/models:/app/api/src/models
- /tank/kokoro/output:/app/output
ports:
- "8765:8880"
environment:
- PYTHONPATH=/app:/app/api
- USE_GPU=true
- PYTHONUNBUFFERED=1
- DOWNLOAD_MODEL=false
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: all
capabilities: [gpu]
networks:
- tnet
labels:
- homepage.group=AI Systems
- homepage.name=Kokoro TTS
- homepage.icon=mdi-waveform
- homepage.description=Kokoro FastAPI TTS (OpenAI-compatible)
- homepage.href=http://10.250.50.54:8765
restart: unless-stopped
networks:
tnet:
name: traefik-net
external: true
>>> /opt/docker/compose/llama-swap/compose.yaml
# llama-swap — GGUF model server with on-demand model swapping.
#
# Proxies OpenAI-compatible API requests to llama.cpp server instances
# and swaps which model is loaded into VRAM per request. Runs on
# ana-ml2 using both GPUs dynamically (no explicit device pinning —
# llama-swap picks per-model-definition).
#
# Model definitions live in /opt/docker/conf/llama-swap/config.yaml on
# the server. Canonical copy of that config is config.yaml in this
# workspace; deploy with scp + `docker compose restart` or the script
# at the bottom of README.md.
#
# All tunables live in .env — edit that, not this file.
services:
llama-swap:
image: ghcr.io/mostlygeek/llama-swap:${LLAMA_SWAP_VERSION}
container_name: llama-swap
restart: unless-stopped
stdin_open: true
tty: true
runtime: nvidia
ports:
- "${LLAMA_SWAP_PORT}:8080"
volumes:
- /opt/docker/conf/llama-swap/config.yaml:/app/config.yaml
- ${MODELS_DIR}:/models
- ${HF_CACHE_DIR}:/hfcache
environment:
- HF_HOME=/hfcache
- HF_HUB_CACHE=/hfcache/hub
# Pin to GPU 0 — the reserved card for on-demand large-model hot-loads.
# The always-on vLLM services (granite + embed/rerank/reward) own GPU 1;
# keeping llama-swap off GPU 1 stops a hot-loaded model from contending
# with them. llama.cpp then sees only GPU 0 (cuda:0), so --n-gpu-layers
# 999 loads there with no per-model device targeting needed.
- NVIDIA_VISIBLE_DEVICES=${LLAMA_SWAP_GPU:-0}
healthcheck:
test: ["CMD-SHELL", "curl -fsS http://localhost:8080/ >/dev/null || exit 1"]
interval: 30s
timeout: 10s
retries: 3
start_period: 30s
networks:
- tnet
labels:
- homepage.group=AI Systems
- homepage.name=llama-swap
- homepage.icon=mdi-swap-horizontal
- homepage.description=GGUF model swapper (llama.cpp; ana-ml2)
- homepage.href=http://10.250.50.54:${LLAMA_SWAP_PORT}
networks:
tnet:
name: traefik-net
external: true
>>> /opt/docker/compose/parakeet/compose.yaml
services:
parakeet-stt:
image: parakeet-stt
ports:
- 8300:8000
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: all
capabilities:
- gpu
restart: unless-stopped
volumes:
- parakeet_cache:/root/.cache
networks:
- tnet
env_file:
- .env
labels:
- homepage.group=AI Systems
- homepage.name=Parakeet
- homepage.icon=mdi-talk
- homepage.description=Parakeet STT (ana-ml2)
- homepage.href=http://10.250.50.54:8300
networks:
tnet:
name: traefik-net
external: true
volumes:
parakeet_cache: null
>>> /opt/docker/compose/qwen35-vl/compose.yaml
# qwen35-vl — Qwen3.5-9B vision-language model (FP8) on ana-ml2.
#
# Co-located on GPU 1 with the granite summarizer + embed/rerank/reward trio
# (GPU 0 is deliberately kept free for hot-reloading large models). Serves on
# :8007, fronted by the LiteLLM gateway as `qwen3.5-9b-fp8`.
#
# WHY A PINNED NIGHTLY DIGEST (not :latest): vLLM :latest (v0.19.1) quantizes
# the Qwen3.5-VL *vision tower* under --quantization fp8, producing garbage
# vision output (the language model is unaffected — it answers text fine but
# "sees" noise). The nightly correctly excludes the vision tower, so vision
# works while the LM still gets the FP8 throughput/VRAM win. We pin the exact
# nightly digest for reproducibility — a moving :nightly tag would silently
# change the engine. WATCH: once the vision-FP8 exclusion lands in a stable
# release, re-pin to :latest and drop this note.
#
# WHY util 0.40 (not the trio's tiny values): the model needs ~34 GB just to
# start at 32k context (FP8 weights + BF16 vision tower + graph capture + 32k
# profiling). On shared GPU 1 (prod uses ~46 GB, ~48 GB free) this vLLM build
# requires free >= util*total, capping util at ~0.51 here; 0.40 (~38 GB) sits
# above the ~34 GB floor with ~10 GB card headroom.
#
# All tunables live in .env — edit that, not this file.
name: qwen35-vl
services:
vllm-qwen35:
image: ${QWEN_IMAGE}
container_name: ${QWEN_CONTAINER_NAME}
restart: unless-stopped
ipc: host
ports:
- "${QWEN_PORT}:8000"
volumes:
- /tank/aimodels/huggingface:/hfcache
environment:
- HF_HOME=/hfcache
- HF_HUB_CACHE=/hfcache/hub
- HUGGING_FACE_HUB_TOKEN=${HF_TOKEN:-}
- VLLM_API_KEY=${API_KEY:-}
command:
- ${QWEN_MODEL}
- --served-model-name
- ${QWEN_SERVED_NAME}
- --quantization
- fp8
- --host
- 0.0.0.0
- --port
- "8000"
- --gpu-memory-utilization
- ${QWEN_GPU_MEM_UTIL}
- --max-model-len
- ${QWEN_MAX_MODEL_LEN}
- --dtype
- auto
# Prefix caching pinned ON (the nightly defaults it OFF). Free win for the
# text-chat path; marginal for vision (each image is a distinct prefix).
- --enable-prefix-caching
deploy:
resources:
reservations:
devices:
- driver: nvidia
device_ids:
- "${QWEN_GPU_ID}"
capabilities:
- gpu
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
interval: 30s
timeout: 10s
retries: 3
start_period: 300s
networks:
- tnet
labels:
- homepage.group=AI Systems
- homepage.name=Qwen3.5-9B VL (FP8)
- homepage.icon=mdi-image-search
- homepage.description=Qwen3.5-9B vision-language (FP8) via vLLM (ana-ml2)
- homepage.href=http://10.250.50.54:${QWEN_PORT}/docs
networks:
tnet:
name: traefik-net
external: true
>>> /opt/docker/compose/vibevoice/compose.yaml
services:
vibevoice:
container_name: vibevoice
deploy:
resources:
reservations:
devices:
- driver: nvidia
count: all
capabilities:
- gpu
ports:
- 8745:8745
volumes:
- /tank/vibevoice/hf:/root/.cache/huggingface
- /tank/vibevoice/voices:/app/voices
- /tank/vibevoice/state:/var/lib/eworker
environment:
- ENABLE_1_5B=true
- ENABLE_LARGE=true
- AUTH_REQUIRED=true
- CORS_ENABLED=true
- ALLOWED_ORIGINS=*
image: eworkerinc/vibevoice:latest
networks:
- tnet
labels:
- homepage.group=AI Systems
- homepage.name=VibeVoice
- homepage.icon=mdi-chat
- homepage.description=EWorkerStudio VibeVoice
- homepage.href=http://10.250.50.54:8745
restart: unless-stopped
networks:
tnet:
name: traefik-net
external: true
>>> /opt/docker/compose/vllm/compose.yaml
# vLLM — Qwen3 Embedding + Reranker + Skywork Reward-V2 classifier.
#
# Originally created to replace the unmaintained Infinity stack (embed +
# rerank); generalized 2026-05-13 to host any vLLM-served model on ana-ml2,
# starting with the Skywork-Reward-V2-Llama-3.1-8B reward classifier
# (AWQ-quantized locally, served from /tank/aimodels/llm/).
#
# vLLM runs one model per process, so this stack brings up three containers
# sharing a single GPU:
#
# vllm-embed — Qwen3-Embedding served as an OpenAI /v1/embeddings server
# vllm-rerank — Qwen3-Reranker served as a /rerank + /score server
# vllm-reward — Skywork-Reward-V2-Llama-3.1-8B-AWQ served as a /classify scorer
#
# The reranker is a causal-LM checkpoint; --hf-overrides re-maps it to
# Qwen3ForSequenceClassification so vLLM's reranking endpoints work and the
# model only emits two class logits (no/yes) instead of the full 151k vocab.
#
# All tunables live in .env — edit that, not this file.
#
# Pre-download models to avoid first-run delay:
# scripts/elway ana-ml2 --playbook playbooks/pull-hf-repo.yaml \
# --var hf_repo=Qwen/Qwen3-Embedding-0.6B
# scripts/elway ana-ml2 --playbook playbooks/pull-hf-repo.yaml \
# --var hf_repo=Qwen/Qwen3-Reranker-0.6B
#
# Skywork-Reward-V2-Llama-3.1-8B-AWQ is a locally-quantized model — lives at
# /tank/aimodels/llm/Skywork-Reward-V2-Llama-3.1-8B-AWQ on ana-ml2 and is
# bind-mounted into the reward service at /local-models. Not from HF Hub.
services:
vllm-embed:
image: vllm/vllm-openai:${VLLM_VERSION}
container_name: vllm-embed
restart: unless-stopped
ipc: host
ports:
- "${EMBED_PORT}:8000"
volumes:
- /tank/aimodels/huggingface:/hfcache
environment:
- HF_HOME=/hfcache
- HF_HUB_CACHE=/hfcache/hub
- HUGGING_FACE_HUB_TOKEN=${HF_TOKEN:-}
- VLLM_API_KEY=${API_KEY:-}
command:
- ${EMBED_MODEL}
- --served-model-name
- ${EMBED_MODEL}
- --runner
- pooling
- --host
- 0.0.0.0
- --port
- "8000"
- --gpu-memory-utilization
- ${EMBED_GPU_MEM_UTIL}
- --max-model-len
- ${EMBED_MAX_MODEL_LEN}
- --dtype
- auto
deploy:
resources:
reservations:
devices:
- driver: nvidia
device_ids:
- "${GPU_ID}"
capabilities:
- gpu
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
interval: 30s
timeout: 10s
retries: 3
start_period: 180s
networks:
- tnet
labels:
- homepage.group=AI Systems
- homepage.name=vLLM Embed (Qwen3)
- homepage.icon=mdi-vector-arrange-below
- homepage.description=Qwen3 Embedding via vLLM (ana-ml2)
- homepage.href=http://10.250.50.54:${EMBED_PORT}/docs
vllm-rerank:
image: vllm/vllm-openai:${VLLM_VERSION}
container_name: vllm-rerank
restart: unless-stopped
ipc: host
ports:
- "${RERANK_PORT}:8000"
volumes:
- /tank/aimodels/huggingface:/hfcache
environment:
- HF_HOME=/hfcache
- HF_HUB_CACHE=/hfcache/hub
- HUGGING_FACE_HUB_TOKEN=${HF_TOKEN:-}
- VLLM_API_KEY=${API_KEY:-}
command:
- ${RERANK_MODEL}
- --served-model-name
- ${RERANK_MODEL}
- --runner
- pooling
- --hf-overrides
- '{"architectures":["Qwen3ForSequenceClassification"],"classifier_from_token":["no","yes"],"is_original_qwen3_reranker":true}'
- --host
- 0.0.0.0
- --port
- "8000"
- --gpu-memory-utilization
- ${RERANK_GPU_MEM_UTIL}
- --max-model-len
- ${RERANK_MAX_MODEL_LEN}
- --dtype
- auto
deploy:
resources:
reservations:
devices:
- driver: nvidia
device_ids:
- "${GPU_ID}"
capabilities:
- gpu
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
interval: 30s
timeout: 10s
retries: 3
start_period: 180s
networks:
- tnet
labels:
- homepage.group=AI Systems
- homepage.name=vLLM Rerank (Qwen3)
- homepage.icon=mdi-sort-variant
- homepage.description=Qwen3 Reranker via vLLM (ana-ml2)
- homepage.href=http://10.250.50.54:${RERANK_PORT}/docs
vllm-reward:
image: vllm/vllm-openai:${VLLM_VERSION}
container_name: vllm-reward
restart: unless-stopped
ipc: host
ports:
- "${REWARD_PORT}:8000"
volumes:
# AWQ output lives in the legacy llama-swap models tree, not the HF cache
# — bind-mount the LLM models dir read-only so the reward service can
# load it as a local-path HF-format model.
- /tank/aimodels/llm:/local-models:ro
environment:
- VLLM_API_KEY=${API_KEY:-}
command:
- /local-models/Skywork-Reward-V2-Llama-3.1-8B-AWQ
- --served-model-name
- Skywork/Skywork-Reward-V2-Llama-3.1-8B-AWQ
# vLLM 0.19.1 deprecated --task in favor of --runner. The model's
# config.json declares `LlamaForSequenceClassification` so the
# pooling runner uses it as a classifier (single-label reward score)
# without needing an explicit task flag.
- --runner
- pooling
- --host
- 0.0.0.0
- --port
- "8000"
- --gpu-memory-utilization
- ${REWARD_GPU_MEM_UTIL}
- --max-model-len
- ${REWARD_MAX_MODEL_LEN}
- --dtype
- auto
deploy:
resources:
reservations:
devices:
- driver: nvidia
device_ids:
- "${GPU_ID}"
capabilities:
- gpu
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
interval: 30s
timeout: 10s
retries: 3
start_period: 240s
networks:
- tnet
labels:
- homepage.group=AI Systems
- homepage.name=vLLM Reward (Skywork)
- homepage.icon=mdi-scale-balance
- homepage.description=Skywork-Reward-V2 8B classifier via vLLM (ana-ml2)
- homepage.href=http://10.250.50.54:${REWARD_PORT}/docs
# Phi-4-mini (FP8) — summarizer + "dreaming" agent. Supersedes the
# llama-swap granite-4-small pin. Generative chat model (OpenAI
# /v1/chat/completions), so NO --runner pooling. FP8 on RTX 6000 Ada
# (cc 8.9): near-lossless, ~1.2x, ~6 GB.
vllm-granite:
image: vllm/vllm-openai:${VLLM_VERSION}
container_name: vllm-granite
restart: unless-stopped
ipc: host
ports:
- "${GRANITE_PORT}:8000"
volumes:
- /tank/aimodels/huggingface:/hfcache
environment:
- HF_HOME=/hfcache
- HF_HUB_CACHE=/hfcache/hub
- HUGGING_FACE_HUB_TOKEN=${HF_TOKEN:-}
- VLLM_API_KEY=${API_KEY:-}
command:
# Production summarizer (replaced phi4-mini 2026-06-05). Default = official
# IBM pre-quantized FP8 (compressed-tensors), loaded directly; FP8 is native
# on the RTX 6000 Ada (cc 8.9). Fallback to vLLM-native dynamic FP8 from
# BF16: GRANITE_MODEL=ibm-granite/granite-4.1-8b + GRANITE_QUANT=fp8.
- ${GRANITE_MODEL}
- --served-model-name
- ${GRANITE_SERVED_NAME}
- --quantization
- ${GRANITE_QUANT}
- --host
- 0.0.0.0
- --port
- "8000"
- --gpu-memory-utilization
- ${GRANITE_GPU_MEM_UTIL}
- --max-model-len
- ${GRANITE_MAX_MODEL_LEN}
- --dtype
- auto
# CUDA graphs ENABLED (no --enforce-eager) for decode throughput. Made
# room 2026-06-05 by right-sizing the embed/rerank/reward trio's KV pools
# (they were over-provisioned at 5.9x/2.0x/3.9x concurrency); GPU 1 now has
# ~17 GB free after granite, so graph-capture buffers fit. If the trio
# ever grows back, granite may need --enforce-eager again on this card.
# FP8 KV cache — halves KV memory; near-lossless on Ada (cc 8.9).
- --kv-cache-dtype
- ${GRANITE_KV_CACHE_DTYPE}
# Prefix caching pinned EXPLICIT (vLLM v1 defaults it on, but pin so a
# version flip can't silently disable it). Benched 2026-06-13: ~6.5x faster
# TTFT (45ms vs 292ms) on a shared ~4.5k-token summarizer template; soft/
# evictable KV, neutral when prefixes don't repeat — pure win for granite.
- --enable-prefix-caching
deploy:
resources:
reservations:
devices:
- driver: nvidia
device_ids:
- "${GRANITE_GPU_ID}"
capabilities:
- gpu
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
interval: 30s
timeout: 10s
retries: 3
start_period: 180s
networks:
- tnet
labels:
- homepage.group=AI Systems
- homepage.name=vLLM Granite 4.1 8B (summarizer)
- homepage.icon=mdi-text-box-outline
- homepage.description=Granite 4.1 8B FP8 via vLLM (ana-ml2)
- homepage.href=http://10.250.50.54:${GRANITE_PORT}/docs
networks:
tnet:
name: traefik-net
external: true
===== CONFIG LAYOUT (/opt/docker/conf/ — top 200 entries) =====
/opt/docker/conf
/opt/docker/conf/llama-swap
/opt/docker/conf/llama-swap/config.yaml
/opt/docker/conf/vllm
===== LISTENING PORTS =====
0.0.0.0:111
0.0.0.0:22
0.0.0.0:5001
0.0.0.0:7007
0.0.0.0:8001
0.0.0.0:8002
0.0.0.0:8003
0.0.0.0:8004
0.0.0.0:8007
0.0.0.0:9292
[::]:111
[::]:22
*:2375
[::]:5001
[::]:8001
[::]:8002
[::]:8003
[::]:8004
[::]:8007
[::]:9292
===== MODEL / HUGGINGFACE CACHES =====
/tank/aimodels/huggingface (342G)
hub entries:
CACHEDIR.TAG
datasets--HuggingFaceH4--ultrachat_200k
datasets--mlabonne--harmful_behaviors
datasets--mlabonne--harmless_alpaca
datasets--Skywork--Skywork-Reward-Preference-80K-v0.2
datasets--wikitext
models--AxionML--Qwen3.5-9B-NVFP4
models--bartowski--Meta-Llama-3.1-8B-Instruct-GGUF
models--bartowski--NousResearch_Hermes-4-14B-GGUF
models--bartowski--TheDrummer_GLM-Steam-106B-A12B-v1-GGUF
models--bartowski--TheDrummer_Skyfall-31B-v4-GGUF
models--BeaverAI--Artemis-31B-v1i-GGUF
models--BeaverAI--Skyfall-R1-31B-v4a-GGUF
models--drawais--Granite-4.1-30B-NVFP4
models--ibm-granite--granite-4.0-h-small-GGUF
models--ibm-granite--granite-4.0-h-tiny-GGUF
models--ibm-granite--granite-4.0-micro-GGUF
models--ibm-granite--granite-4.1-8b
models--ibm-granite--granite-4.1-8b-fp8
models--llmfan46--Qwen3.6-35B-A3B-uncensored-heretic-GGUF
models--microsoft--Phi-4-mini-instruct
models--mradermacher--Daredevil-8B-abliterated-dpomix-GGUF
models--mradermacher--Qwen3-30B-A3B-abliterated-erotic-i1-GGUF
models--mradermacher--Qwen3.6-35B-A3B-abliterated-i1-GGUF
models--mradermacher--Selene-1-Mini-Llama-3.1-8B-i1-GGUF
models--murilonwt--granite-4.1-8b-NVFP4
models--newsletter--VibeVoice-Large-pt
models--Qwen--Qwen2.5-0.5B-Instruct
models--Qwen--Qwen3.5-9B
models--Qwen--Qwen3.6-35B-A3B
/tank/aimodels/llm (794G)
/home/lkraven/.cache/huggingface (15G)
hub entries:
CACHEDIR.TAG
datasets--Salesforce--wikitext
datasets--Skywork--Skywork-Reward-Preference-80K-v0.2
datasets--wikitext
models--Astralyra--bge-reranker-large-Q8_0-GGUF
models--ggml-org--embeddinggemma-300M-GGUF
models--ggml-org--Qwen3-Reranker-0.6B-Q8_0-GGUF
models--jinaai--jina-reranker-v3-GGUF
models--klnstpr--bge-reranker-v2-m3-Q8_0-GGUF
models--minhtd14--jina-reranker-v2-base-multilingual-Q8_0-GGUF
models--Mungert--Qwen3-Reranker-0.6B-GGUF
models--Qwen--Qwen3-Embedding-0.6B-GGUF
models--Qwen--Qwen3-Reranker-0.6B
models--Skywork--Skywork-Reward-V2-Llama-3.1-8B
models--unsloth--gemma-4-26B-A4B-it
models--unsloth--gemma-4-26B-A4B-it-GGUF
models--unsloth--gemma-4-31B-it-GGUF
===== DOCKER-ADJACENT SYSTEMD SERVICES =====
containerd.service running
docker.service running
nvidia-persistenced.service running
===== DONE =====
Paste the above back into the chat, or pass a path as argv[1] to save.
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