nimble
4 TagsUpdated Apache-2.0by Bespoke Labs
Decision model by Bespoke Labs: a LoRA on Qwen3.5-9B trained on contrastive pairs. Nimble reads the whole request as a JSON schema and scores each option by the next-token logit of its code; Ollaya applies the author's temperature, so its probabilities are calibrated. Up to 255 options.
decisionfine-tuned9b
Tags
| Name |
|---|
| nimblelatestSame as nimble:9b.19.5 GB · 8192 ctx · English |
| nimble:9bBespoke-Nimble-9B v2 (LoRA on Qwen3.5-9B) with the author's temperature 2.18. Needs a 24 GB GPU.19.5 GB · 8192 ctx · English |
| nimble:9b-fp16Bespoke Labs' Nimble v2: a LoRA on Qwen3.5-9B that answers every question from the next-token logits of its option codes, calibrated with the author's temperature. Up to 255 options. Needs about 18 GB of memory; best on a 24 GB GPU. This tag computes in fp16 on NVIDIA GPUs: faster than nimble:9b, with at least 99.5 % of its decisions the same. On a CPU it runs, slowly; use nimble:9b there.19.5 GB · 8192 ctx · English |
| nimble:9b-v3Bespoke-Nimble-9B v3: v2's prompts with a new LoRA, served as the author's Decision Index engine. CC BY-NC 4.0 (non-commercial). Needs a 24 GB GPU.20.0 GB · 32768 ctx · English |
Tags without a suffix load fp16 on a CUDA GPU and fp32 on CPU; add -fp16 or -fp32 to pin one precision.