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circuitforge-core/tests/test_hardware
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feat(hardware): add model_vram_estimate for model-to-hardware VRAM fit checks 
Answers "can this hardware run model X at quantization level Y?" by
querying the HuggingFace Hub API for parameter count (safetensors) and
architecture (config.json), then applying the standard VRAM formula:
weights + KV cache (GQA-aware) + overhead. Reference algorithm from
LLMcalc (no code copied, unlicensed upstream).

Bump to 0.22.0.

Closes: #64
2026-07-10 17:44:36 -07:00
..
__init__.py feat: hardware detection, cf-docuvision service, documents ingestion pipeline 2026-04-02 18:53:25 -07:00
test_detect.py feat: hardware detection, cf-docuvision service, documents ingestion pipeline 2026-04-02 18:53:25 -07:00
test_generator.py feat: hardware detection, cf-docuvision service, documents ingestion pipeline 2026-04-02 18:53:25 -07:00
test_tiers.py feat: hardware detection, cf-docuvision service, documents ingestion pipeline 2026-04-02 18:53:25 -07:00
test_vram_estimate.py feat(hardware): add model_vram_estimate for model-to-hardware VRAM fit checks 2026-07-10 17:44:36 -07:00