AI is happening. The future is updating.Wald-4B-GGUF
GGUF files of Wald-Q4B v2.1 (tag `v2.1`) for llama.cpp: an open 4B decision model that returns a calibrated probability for every option. - One pass, text only: the bundled server reads a probability for every option from the model's option-letter logits (Qwen chat template), calibrated with the same frozen temperature table as the BF16 release. - `--effort auto` (Auto 0.7) also runs here but has not been parity-checked on GGUF; for images, use the BF16 release. - On a 1,000-request Decision Index sample (5,922 questions), Q8_0 gives the BF16 answer on 99.5 % of questions and Q4_K_M on 97.3 %. All numbers: evaluation/v2.1-gguf-parity.json. - v2 (`Wald-4B-v2-*.gguf`, `v2/`): Wald-Q4B v2, unchanged in this repository. - v1.2 (`Wald-4B-v1.2-*.gguf`, `server/`): unchanged in this repository.
GGUF files of Wald-Q4B v2.1 (tag `v2.1`) for llama.cpp: an open 4B decision model that returns a calibrated probability for every option. - One pass, text only: the bundled server reads a probability for every option from the model's option-letter logits (Qwen chat template), calibrated with the same frozen temperature table as the BF16 release. - `--effort auto` (Auto 0.7) also runs here but has not been parity-checked on GGUF; for images, use the BF16 release. - On a 1,000-request Decision Index sample (5,922 questions), Q8_0 gives the BF16 answer on 99.5 % of questions and Q4_K_M on 97.3 %. All numbers: evaluation/v2.1-gguf-parity.json. - v2 (`Wald-4B-v2-*.gguf`, `v2/`): Wald-Q4B v2, unchanged in this repository. - v1.2 (`Wald-4B-v1.2-*.gguf`, `server/`): unchanged in this repository.