Grant
72bf754baa
- Move models.yaml into image/ so the docker build context is self-contained - Fix manifest: dockerfile=../image/Dockerfile, workdir=../image - Add LICENSE (MIT) and assets/README.md (StartOS marketplace listing) - s9pk validates: id=spark-control, version=0.1.0:0, osVersion=0.4.0-beta.6, sdkVersion=1.3.3 - Image embeds python:3.12-slim + openssh-client + FastAPI app + models.yaml
87 lines
2.3 KiB
YAML
87 lines
2.3 KiB
YAML
# spark-control model catalog
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#
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# Edit this file (or override at runtime via the StartOS "Edit Model Catalog"
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# action) to add or change available models.
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#
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# Each model entry produces this command on Spark 1:
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# cd ~/spark-vllm-docker
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# ./launch-cluster.sh [--solo] -d exec vllm serve <repo> \
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# --port=<defaults.port> --host=<defaults.host> <vllm_args...>
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defaults:
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port: 8888
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host: 0.0.0.0
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models:
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qwen3-vl:
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display_name: "Qwen3-VL 235B (vision)"
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repo: RedHatAI/Qwen3-VL-235B-A22B-Instruct-NVFP4
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size_gb: 135
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mode: cluster
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capabilities: [vision, multilingual]
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expected_ready_seconds: 300
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vllm_args:
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- --gpu-memory-utilization=0.7
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- -tp=2
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- --distributed-executor-backend=ray
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- --max-model-len=32768
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gemma4:
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display_name: "Gemma 4 31B"
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repo: RedHatAI/gemma-4-31B-it-NVFP4
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size_gb: 23
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mode: solo
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capabilities: [vision, reasoning, tools]
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expected_ready_seconds: 240
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vllm_args:
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- --gpu-memory-utilization=0.8
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- --max-model-len=32768
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- --reasoning-parser=gemma4
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- --tool-call-parser=gemma4
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- --enable-auto-tool-choice
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- --load-format=fastsafetensors
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- --enable-prefix-caching
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- --kv-cache-dtype=fp8
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qwen36:
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display_name: "Qwen3.6 35B-A3B (daily driver)"
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repo: RedHatAI/Qwen3.6-35B-A3B-NVFP4
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size_gb: 20
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mode: solo
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capabilities: [reasoning]
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expected_ready_seconds: 300
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vllm_args:
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- --gpu-memory-utilization=0.85
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- --max-model-len=65536
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- --reasoning-parser=qwen3
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- --moe_backend=flashinfer_cutlass
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- --load-format=fastsafetensors
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- --enable-prefix-caching
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- --kv-cache-dtype=fp8
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qwen3-235b-fp8:
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display_name: "Qwen3 235B-A22B FP8 (legacy)"
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repo: Qwen/Qwen3-235B-A22B-FP8
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size_gb: 220
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mode: cluster
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capabilities: []
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expected_ready_seconds: 360
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vllm_args:
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- --gpu-memory-utilization=0.7
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- -tp=2
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- --distributed-executor-backend=ray
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- --max-model-len=32768
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qwen25-72b:
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display_name: "Qwen2.5 72B (legacy)"
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repo: Qwen/Qwen2.5-72B-Instruct
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size_gb: 145
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mode: cluster
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capabilities: []
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expected_ready_seconds: 360
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vllm_args:
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- --gpu-memory-utilization=0.7
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- -tp=2
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- --distributed-executor-backend=ray
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- --max-model-len=32768
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