GGUF / llama.cpp build of Hanno-Labs/dinghy-law-8b-v1, a multilingual legal text-embedding model with 8B parameters, derived from nvidia/Nemotron-3-Embed-8B-BF16. Source revision 8a2d25a2c845f0e3001e3198c71b2a0db4eee27e.

Q8_0 is the recommended default when memory permits. Q6_K trades a smaller footprint for modest additional quantization error. Q4_K_M is the compact option; use the measured fidelity below when choosing.

This is a non-causal Ministral3 bidirectional encoder embedding model with mask-aware mean pooling, 4096-dimensional L2-normalized embeddings, and an 8192-token published context cap. The conversion preserves the source model's is_causal: false setting in GGUF metadata.

The GGUF tokenizer metadata sets automatic BOS insertion to false and automatic EOS insertion to false. These values match the source tokenizer; do not add special tokens manually.

The source Sentence Transformers package ends with a 4096-dimensional Dense projection. llama.cpp does not carry that post-pooling projection, so this release uses the backbone geometry: Transformer -> mean pool -> L2 normalize. On the frozen multilingual legal probes, cosine between the full HF package and the backbone-only representation is 0.99638 mean / 0.99251 minimum. The table below separately reports each quant against both the backbone and the full public model.

Queries must begin with query: and documents with passage: . These are semantic roles used during training and evaluation, not optional display labels.

The probe set includes query and document roles in English, German, and Chinese plus an 8192-token legal-document probe. The release job must pass its declared per-quant thresholds before any repository is made public.

Query embedding:

Document embedding:

The full Sentence Transformers model scores 72.58 Mean(Task) nDCG@10 on MTEB(Law, v1). That benchmark number describes the full HF package; the GGUF variants are documented by direct embedding-fidelity measurements above.

Converted from the immutable source revision with the official llama.cpp converter and quantizer. Converter source commit: 5f55650a7. Container: ghcr.io/ggml-org/llama.cpp@sha256:c44fb21e7342c21d22f74516aafb47294bf5b5886a929ccc67f9325c67b39b9d.

The legal training data and adaptation process are public in the source model repository. License: openmdw-1.1. The complete license text and origin notices are included in LICENSE and NOTICE.