Experts now stay MXFP4-packed on GPU (~10GB whole model, fits one 32GB
card) instead of dequantized to ~38GB BF16. loader::load_model_dir_split
returns BF16 tensors + raw U8 (_blocks/_scales) in one pass; GptOss slices
each expert's MXFP4 bytes to a GpuBuffer at load, and expert_forward
dequantizes the selected expert to a BF16 scratch (dequant_mxfp4) right
before its GEMM — no per-token CPU->GPU upload, no 38GB BF16 dir.
Verified: gptoss-logits on the original MXFP4 dir
(/opt/wjh/models/gpt-oss-20b) gives logits byte-identical to the BF16 path
— top-1 token 12650 = " Paris" @ 15.3125, full top-10 unchanged — running
on a single GPU. Build green on dash5 (release).
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Phase 6 — Model Loading (xserv-model):
- safetensors parser with single/sharded file support
- ModelConfig with dual naming (GPT-2 n_embd/n_head + modern HF naming)
- Weight loading flow: safetensors → mmap → CPU Tensor → GPU
Phase 7 — BPE Tokenizer (xserv-tokenizer):
- Full BPE encode/decode from tokenizer.json
- GPT-2 byte-to-unicode mapping (printable ASCII identity + shifted bytes)
- Pre-tokenization regex, special token handling
- Chat template support structure
Phase 8 — GPT-2 Complete Inference:
- GPT-2 model definition: wte, wpe, 12 transformer blocks, ln_f
- Forward pass: embedding → (LayerNorm → MHA → residual → LayerNorm → MLP → residual) × 12 → LN → logits
- QKV split with correct [batch, heads, seq, dim] layout (fixed reshape bug)
- Greedy sampling from last-position logits
- Interactive CLI: xserv-cli <model-dir> [--max-tokens N]
Verified: GPT-2 124M generates coherent English text on RTX 5090.
"The future of AI is uncertain. The future of AI is uncertain..."
"Once upon a time, the world was a place of great beauty..."
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
