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README.md

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+---
+language:
+- multilingual
+license: apache-2.0
+base_model:
+- ibm-granite/granite-embedding-311m-multilingual-r2
+library_name: llama.cpp
+pipeline_tag: sentence-similarity
+tags:
+- gguf
+- llama.cpp
+- embeddings
+- multilingual
+- retrieval
+- rag
+- sentence-transformers
+- granite
+- modernbert
+---
+
+# Granite Embedding 311M Multilingual R2 - GGUF
+
+This repository provides a GGUF conversion of the IBM Granite embedding model:
+
+**Base model:** `ibm-granite/granite-embedding-311m-multilingual-r2`
+
+Original model card:
+https://huggingface.co/ibm-granite/granite-embedding-311m-multilingual-r2
+
+## Model Description
+
+Granite Embedding 311M Multilingual R2 is a multilingual embedding model developed by IBM for semantic search, retrieval, RAG, clustering, and similarity tasks.
+
+Key features:
+
+- Multilingual support
+- 311M parameters
+- 768-dimensional embeddings
+- Up to 32k context length
+- Optimized for retrieval and semantic similarity
+- Compatible with llama.cpp through GGUF conversion
+
+## Files
+
+| File | Precision | Recommended Use |
+|------|-----------|-----------------|
+| `granite-embedding-311m-multilingual-r2-F16.gguf` | F16 | Maximum quality and accuracy |
+
+## Conversion Details
+
+This GGUF file was generated using the official `llama.cpp` conversion tools.
+
+### Conversion command
+
+```bash
+python convert_hf_to_gguf.py \
+    granite-embedding-311m-multilingual-r2 \
+    --outfile granite-embedding-311m-multilingual-r2-F16.gguf \
+    --outtype f16
+```
+
+### llama.cpp version
+
+```text
+Commit: 96fbe0039337a999613a983d66e2bfcc4bb554d7
+```
+
+## Usage with llama.cpp
+
+### Embedding generation
+
+```bash
+llama-embedding \
+    -m granite-embedding-311m-multilingual-r2-F16.gguf \
+    -p "Artificial intelligence is transforming software engineering."
+```
+
+### OpenAI-compatible server
+
+```bash
+llama-server \
+    -m granite-embedding-311m-multilingual-r2-F16.gguf \
+    --embedding
+```
+
+Example request:
+
+```bash
+curl http://localhost:8080/v1/embeddings \
+    -H "Content-Type: application/json" \
+    -d '{
+        "input": "Hello world"
+    }'
+```
+
+## Intended Uses
+
+This model is suitable for:
+
+- Retrieval-Augmented Generation (RAG)
+- Semantic search
+- Document retrieval
+- Similarity search
+- Clustering
+- Deduplication
+- Cross-lingual retrieval
+- Recommendation systems
+
+## Notes
+
+This repository only provides a GGUF conversion of the original IBM model. All credit for the model architecture, training, and evaluation belongs to IBM Research.
+
+Please refer to the original model card for:
+
+- Training details
+- Evaluation results
+- Benchmark scores
+- Limitations
+- Responsible AI considerations
+
+Original repository:
+
+https://huggingface.co/ibm-granite/granite-embedding-311m-multilingual-r2
+
+## License
+
+This GGUF conversion is distributed under the same license as the original model:
+
+**Apache License 2.0**
+
+Please verify license compatibility with your intended use case.
+
+## Acknowledgements
+
+- IBM Research for developing the Granite Embedding model.
+- The llama.cpp project for GGUF support and inference.
+- The Hugging Face community for model hosting and distribution.

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