parity-embedding-juridico-br-v1: initial fine-tune

.gitattributes

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+onnx/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

1_Pooling/config.json

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README.md

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+---
+language:
+- pt
+license: apache-2.0
+library_name: sentence-transformers
+tags:
+- sentence-transformers
+- feature-extraction
+- legal
+- portuguese
+- brazilian
+- licitacao
+- procurement
+base_model: sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
+pipeline_tag: feature-extraction
+---
+
+# parity-embedding-juridico-br-v1
+
+Embedding model fine-tuned for the Brazilian legal/procurement domain
+(licitações, Lei 14.133/21, jurisprudência TCU, captação de capital
+sustentável). Built on top of `paraphrase-multilingual-MiniLM-L12-v2`
+(384 dim, 33M params).
+
+## Training
+
+- **Base model**: sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
+- **Dataset**: Triplets mined from Parity's curated knowledge base
+  (TCU acórdãos + súmulas, Lei 14.133/21 articles, IN SEGES, decretos).
+- **Loss**: `MultipleNegativesRankingLoss` (in-batch contrastive).
+- **Strategy**: self-positives (tese vs textoChave of same acórdão) +
+  category-positives (acórdãos in same legal category) + hard negatives
+  (top vector-similar acórdãos from different categories).
+
+## Usage
+
+### Sentence-Transformers (Python)
+
+```python
+from sentence_transformers import SentenceTransformer
+m = SentenceTransformer("SamuelMauli/parity-embedding-juridico-br-v1")
+v = m.encode("Acórdão 244/2021 limita atestado quantitativo a 50%")
+```
+
+### @xenova/transformers (JavaScript / Node / Browser)
+
+```ts
+import { pipeline } from "@xenova/transformers";
+const pipe = await pipeline(
+  "feature-extraction",
+  "SamuelMauli/parity-embedding-juridico-br-v1"
+);
+const out = await pipe("texto jurídico", { pooling: "mean", normalize: true });
+```
+
+## Caveats
+
+- Trained on a small (~130 triplets), domain-narrow dataset.
+- Excellent for retrieval among TCU acórdãos and Brazilian procurement
+  literature; **do NOT use for general-purpose embedding tasks**.
+- Output dim: 384 (preserves compatibility with `vector(384)` in pgvector).
+
+## Citation
+
+Maintained by Doublethree / Parity (samuel.mauli@gmail.com).

config.json

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config_sentence_transformers.json

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+  },
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+  "similarity_fn_name": "cosine"
+}

eval/triplet_evaluation_parity-v4-eval_results.csv

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+1.0,133,0.9821428656578064
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modules.json

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