Update README.md

README.md

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----
-license: apache-2.0
----
+---
+tags:
+- mteb
+- sentence-transformers
+- transformers
+- multilingual
+- sentence-similarity
+license: apache-2.0
+---
+
+## gte-multilingual-base
+
+The **gte-multilingual-base** model is the latest in the [GTE](https://huggingface.co/collections/Alibaba-NLP/gte-models-6680f0b13f885cb431e6d469) (General Text Embedding) family of models, featuring several key attributes:
+
+- **High Performance**: Achieves state-of-the-art (SOTA) results in multilingual retrieval tasks and multi-task representation model evaluations when compared to models of similar size.
+- **Training Architecture**: Trained using an encoder-only transformers architecture, resulting in a smaller model size. Unlike previous models based on decode-only LLM architecture (e.g., gte-qwen2-1.5b-instruct), this model has lower hardware requirements for inference, offering a 10x increase in inference speed.
+- **Long Context**: Supports text lengths up to **8192** tokens.
+- **Multilingual Capability**: Supports over **70** languages.
+- **Elastic Dense Embedding**: Support elastic output dense representation while maintaining the effectiveness of downstream tasks, which significantly reduces storage costs and improves execution efficiency.
+- **Sparse Vectors**: In addition to dense representations, it can also generate sparse vectors.
+
+## Model Information
+- Model Size: 304M
+- Embedding Dimension: 768
+- Max Input Tokens: 8192
+
+## Requirements
+```
+transformers>=4.39.2
+flash_attn>=2.5.6
+```
+## Usage