Model reference · open weights
gte-multilingual-reranker is an open-weight embedding model from Alibaba-NLP, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.
About
gte-multilingual-reranker-base The gte-multilingual-reranker-base model is the first reranker model in the GTE 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 reranker 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. Model Information - Model Size: 306M - Max Input Tokens: 8192 Usage - It is recommended to install xformers and enable unpadding for acceleration, refer to enable-unpadding-and-xformers. - How to use it offline: new-impl/discussions/2 Using Huggingface transformers (transformers=4.36.0) Usage with infinity: Infinity, a MIT Licensed Inference RestAPI Server. Usage with Text Embeddings Inference (TEI): - CPU: - GPU: Then you can send requests to the deployed API via the /rerank route (see the Text Embeddings Inference OpenAPI Specification for more details): Evaluation Results of reranking based on multiple text retreival datasets More detailed experimental results can be found in the paper. Cloud API Services In addition to the open-source GTE series models, GTE series models are also available as commercial API services on Alibaba Cloud. - Embedding Models: Three versions of the text embedding models are available: text-embedding-v1/v2/v3, with v3 being the latest API service. - ReRank Models: The gte-rerank model service is available. Note that the models behind the commercial APIs are not entirely identical to the open-source models. Citation If you find our paper or models helpful, please consider cite:
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | Alibaba-NLP |
|---|---|
| Type | Embedding models |
| Parameters (lead) | 306M |
| Context | 8k tokens |
| Variants | 1 |
| Runs with | sentence-transformers |
| Released | 2024-07-20 |
| Popularity | 691k downloads / month |
| Likes | 189 |
| Licence | Open weights |
How it works
Variants
Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.
| Variant | Params | Precision | VRAM | Fits 16 GB | Weights |
|---|---|---|---|---|---|
| gte-multilingual-reranker-base | 306M | BF16 | ~0.7 GB | ✓ | Weights ↗ |
Using it via the API
Once AxForge deploys gte-multilingual-reranker for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (gte-multilingual-reranker below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/embeddings \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"gte-multilingual-reranker","input":"text to embed"}'
Licence
Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗
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