bespokelabsai/nimble
Local typed decisions, contrastive data curation, and model evaluation.
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README & documentation
Source previewRead the project’s overview, installation instructions and usage examples. The original README is the source of truth.
Data, Model, Recipe for an open Jev Model · Capabilities · Quickstart · Methodology · Documentation and development · Citation Nimble takes some text and a schema, and makes typed decisions about the text. The schema is the list of questions to answer. Each question is either a choice from a list that you give or a true or false question. For each question, Nimble returns the answer it picked and the probability of each allowed answer. Nimble makes each decision in one step and does not write out any reasoning first, so it is fast (blazing fast!). Nimble is inspired by the System One approach of TypeSafe's Jev. In this repository, we share our recipe for training such a model. Note that we did not distill from Jev. The point of the repository is to show how to curate data, how to train, and to serve such a model,…
Read the full README ↗ · Preview checked 2026-09-20T07:23:42.056Z
Inside the original README — Document outline
- Bespoke Nimble
- Capabilities
- What you can build
- What you cannot build with the current release
- Quickstart
- Download the model
- Mac with Apple Silicon (MLX)
- Linux with an NVIDIA GPU (CUDA)
- Make a typed decision
- Methodology
- Serving
- Contrastive data curation
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What this repository does
Local typed decisions, contrastive data curation, and model evaluation.
Repository facts
- Owner
- bespokelabsai
- Primary language
- Python
- Stars
- 1,267
- Forks
- 89
- Open issues + pull requests
- 2
- License
- Not reported — inspect the license file
- Archived
- No
- Default branch
- main
- Created
- 2026-09-18T09:07:48.000Z
- Last push
- 2026-09-20T19:44:35.000Z
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