mirror of
https://github.com/elder-plinius/OBLITERATUS.git
synced 2026-08-17 16:37:30 +02:00
Brian Bell
62b006f6c4
Point obliteratus at an FP8 or NVFP4 checkpoint and it just works: the loader detects the format from config.json + safetensors metadata (no weight loads), dequantizes shard-by-shard to a temporary BF16 copy, then runs the normal float pipeline and saves BF16. Supported layouts: - FP8 DeepSeek-style block-wise (weight_scale_inv + weight_block_size) - FP8 per-channel / per-tensor (compressed-tensors, ModelOpt) - NVFP4 ModelOpt (uint8 nibbles + FP8 group scales + FP32 global), including MIXED_PRECISION checkpoints (FP8 mixer + NVFP4 experts) - NVFP4 compressed-tensors (reciprocal scales) Design: - New pure-torch obliteratus/models/quant_dequant.py; no new deps. NVFP4 unpack uses torch.float4_e2m1fn_x2 when a runtime probe proves it works, else a chunked nibble LUT (bounds transient int64 index memory; a naive implementation OOMed at 96GB on a 30B model). - Scale keys are dropped only when their base weight exists in the same shard, so legitimate params ending in _scale (logit_scale et al.) survive. - Unsupported schemes (fbgemm, quanto, W4A4, ...) fail loudly at load, naming the scheme. - Surgery guards: float8 or packed uint8 reaching _dequantize_weight or any fused-MoE path raises RuntimeError instead of silently upcasting (bitsandbytes quant_state params are explicitly excluded). - Save path strips quantization metadata and logs that output is BF16; re-quantization for serving is out of scope (llm-compressor/modelopt). - CLI: new --trust-remote-code flag; help text documents auto-detection. Validated end-to-end on 1x A100-80GB (see PR description): Nemotron-3-Nano-Omni-30B NVFP4 (mixed) and FP8, Qwen3-8B-FP8 (block-wise) vs Qwen3-8B BF16 baseline (perplexity 4.23 vs 4.33).