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README.md

@@ -42,11 +42,14 @@ We serve:
 
 We publish the datasets and components that power our research openly wherever we can.
 
+### Models
+- [**`judicialmind/greenleaf-law-embed-tiny`**](https://huggingface.co/judicialmind/greenleaf-law-embed-tiny) — 596M-parameter dense embedding model purpose-built for legal text retrieval. Scores **78.3% on MLEB-12** and **64.4% on MTEB(Law, v1)** — competitive with models 13x larger. Bidirectional attention, 1024-dim embeddings, 32K context, built-in int8/binary quantization. Apache 2.0.
+
+_More models coming soon — reranking and legal-reasoning models trained on our corpus._
+
 ### Datasets
 - [**`judicialmind/legal-training-dataset`**](https://huggingface.co/datasets/judicialmind/legal-training-dataset) — 3.69M annotated query-passage pairs across **35 languages** for training legal IR, QA, and semantic-search models. Rich metadata per row: `query_type`, `legal_domain`, `difficulty`, `jurisdiction`. ~2.6 GB, 264 parquet shards, A/B/C file-level split for clean train/val/test partitioning.
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-### Models
-_Coming soon — we are releasing family of fine-tuned retrieval, reranking, and legal-reasoning models trained on our corpus._
+- [**`judicialmind/india-acts`**](https://huggingface.co/datasets/judicialmind/india-acts) — Comprehensive corpus of Indian Acts and legislation for legal retrieval, NLP, and downstream legal AI tasks.
 
 ### Spaces
 _Coming soon — interactive demos for legal retrieval, agent workflows, and dispute-resolution tooling._