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smoky1496
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smoky1496
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bash
docker run --gpus all -p 8000:8000 --ipc=host vllm/vllm-openai:v0.10.2 \ --model smoky1496/SpawnPoint-Coder-7B-AWQ --served-model-name SpawnPoint-Coder-7B --max-model-len 16384 --gpu-memory-utilization 0.85Then Spawn Point finds it automatically at http://localhost:8000/v1.
Same prompts, schemas, normalizer and server for both versions. The sealed set for the new game kinds was written before training and not looked at until the release decision. Human-written prompts are English and Vietnamese.
| benchmark | v3 | v4 (this release) |
|---|---|---|
| sealed set for the new game kinds (12 prompts), fully right | 50% | 67% |
| 16 human-written prompts for the new game kinds, fully right | 50% | 75% |
| held-out briefs for the new game kinds (exact) | 32% | 91% |
| sealed set for the older game kinds (12 prompts), fully right | 67% | 67% |
| 30 human-written prompts, fully right | 87% | 87% |
| 12 prompts for bubble / rescue / survivor games, fully right | 75% | 92% |
| held-out brief (exact) | 85% | 81% |
| held-out tweak (exact) | 84% | 100% |
| held-out entity (exact) | 100% | 100% |
| held-out translate (exact) | 97% | 97% |
The 4-bit AWQ files you download, measured the same way (fully right):
| benchmark | v3 AWQ | v4 AWQ |
|---|---|---|
| sealed set, new game kinds | 33% | 75% |
| 16 prompts, new game kinds | 44% | 88% |
| 30 human-written prompts | 90% | 90% |
Apache 2.0, see LICENSE and NOTICE.
docker run --gpus all -p 8000:8000 --ipc=host vllm/vllm-openai:v0.10.2 \ --model smoky1496/SpawnPoint-Coder-7B-AWQ --served-model-name SpawnPoint-Coder-7B --max-model-len 16384 --gpu-memory-utilization 0.85