Rneg-d-r50b-r50.03 Update ((new)) 🎯

With production deployment in mind, the Rneg-d-r50b-r50.03 Update incorporates quantization-aware training (QAT) layers. Previously, users had to train in FP32 and then separately quantize to INT8, often suffering a 1-2% drop in recall@10.

If you are using a model hub (e.g., Hugging Face), run: Rneg-d-r50b-r50.03 Update

: Corrects estimated time of arrival (ETA) underestimations and radar speed calculations for vehicles using miles as their primary unit. With production deployment in mind, the Rneg-d-r50b-r50

[Insert link to model/weights]