| --- |
| license: cc-by-nc-sa-4.0 |
| base_model: naver/splade-v3 |
| tags: |
| - splade |
| - sparse-retrieval |
| - gguf |
| - crispembed |
| library_name: crispembed |
| --- |
| |
| # SPLADE-v3 — GGUF (CrispEmbed) |
|
|
| GGUF conversions of [`naver/splade-v3`](https://huggingface.co/naver/splade-v3) |
| for sparse (learned-lexical) retrieval with |
| [CrispEmbed](https://github.com/CrispStrobe/CrispEmbed) — a dependency-free |
| C/C++ embedding runtime (`--sparse` mode / `crispembed_encode_sparse`). |
|
|
| SPLADE produces a **sparse** vector of weighted vocabulary term expansions |
| (`log(1 + ReLU(MLM_logits))`, max-pooled over tokens), not a dense embedding. |
|
|
| ## Files |
|
|
| | File | Quant | Size | Sparse-cos vs HF fp32 | |
| |------|-------|------|-----------------------| |
| | `splade-v3-iq4_xs.gguf` | IQ4_XS + imatrix | 68 MB | 0.9971 (compact default) | |
| | `splade-v3-q8_0.gguf` | Q8_0 | 111 MB | 1.0000 | |
| | `splade-v3-f16.gguf` | F16 | 256 MB | 1.0000 (precision control) | |
| |
| Sparse-cos = cosine over the full 30522-dim vocabulary term-weight vector vs |
| the original PyTorch `naver/splade-v3` (`BertForMaskedLM` + SPLADE pooling), |
| averaged over a probe set. The IQ4_XS build uses a CrispEmbed importance matrix |
| collected over a calibration corpus. The MLM/SPLADE head is preserved and |
| verified present in every quant. |
|
|
| ## Usage |
|
|
| ```bash |
| crispembed -m splade-v3-iq4_xs.gguf --sparse "your query text" |
| # → token_id weight (one per expansion term) |
| ``` |
|
|
| ## License & attribution |
|
|
| Derived from [`naver/splade-v3`](https://huggingface.co/naver/splade-v3), |
| licensed **CC-BY-NC-SA-4.0** (non-commercial, share-alike). These GGUF |
| conversions inherit the same license: **non-commercial use only**, attribution |
| to Naver required, and derivatives must be shared alike. See the base model |
| card and the SPLADE papers for citation. |
|
|
| ## Provenance and EU AI Act Art. 53 note |
|
|
| - **Upstream model:** [naver/splade-v3](https://huggingface.co/naver/splade-v3) — published by `naver`. |
| - **Upstream licence:** `cc-by-nc-sa-4.0`. This repository redistributes under the same terms; it grants no rights the upstream licence does not. |
| - **What was done here:** format conversion and/or quantisation only (GGUF). No training, no fine-tuning, no merging, no distillation, no change to architecture, vocabulary or capability. Only the numeric representation of the upstream weights differs. |
| - **Training data:** documented — where it is documented at all — by the upstream provider; see the upstream model card. No training data was used, added or selected by this repository. No training-content summary was found on the upstream model card at the time of writing; that documentation gap is upstream's and is not filled here. |
| - **Provider status:** under Regulation (EU) 2024/1689 the upstream authors remain the provider of this model. Converting the serialisation format does not make this repository the provider of a new general-purpose AI model, and no such claim is made. Questions about training content, copyright policy or model capability belong upstream. |
|
|
