swactor/apps/pipeline-parallel-inference/profiles/vastai.env

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# WAN run on leased vast.ai GPUs. Copy to profiles/local.env and fill in the
# relay URL + image; keep that copy untracked.
#
# PP_PROFILE=profiles/local.env cargo run --bin pp-orchestrator -- \
# --vastai --api-key "$VASTAI_API_KEY"
#
# All nodes home onto one operator-controlled relay so they can hole-punch /
# fall back to relaying across the public internet.
# Required for WAN: the relay every container connects through. PLACEHOLDER —
# replace with your swactor-iroh-relay endpoint in profiles/local.env.
SWACTOR_IROH_RELAY_URL=https://relay.example.com
NUM_STAGES=2
PP_IMAGE=swactor-pp-gpu:latest
# GPU filters are optional. Leave both unset to let any verified 1-GPU offer
# qualify (a 1B model fits anywhere). Set PP_GPU="RTX 3060" to pin a model, and/or
# PP_GPU_MIN_RAM_MB=8000 to require a VRAM floor.
# llama3.2:1b -> HF Llama-3.2-1B-Instruct-Q6_K.gguf (16 blocks, sharded across
# the N stages by compute_layer_range; validated key baked into the image).
MODEL=llama3.2:1b
MAX_TOKENS=64