Model reference · open weights

cross-encoder-russian-msmarco

cross-encoder-russian-msmarco is an open-weight embedding model from DiTy, 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.

Embeddings DiTy 1 variants 78k downloads/mo
Request this model on EU hardware All served models Not on the shared API today — deployed on request.

About

What cross-encoder-russian-msmarco is

DiTy/cross-encoder-russian-msmarco This is a sentence-transformers model based on a pre-trained DeepPavlov/rubert-base-cased and finetuned with MS-MARCO Russian passage ranking dataset. The model can be used for Information Retrieval in the Russian language: Given a query, encode the query will all possible passages (e.g. retrieved with ElasticSearch). Then sort the passages in a decreasing order. See SBERT.net Retrieve & Re-rank for more details. Usage (Sentence-Transformers) Using this model becomes easy when you have sentence-transformers installed: Then you can use the model like this: Usage (HuggingFace Transformers) Without sentence-transformers, you can use the model like this: First, you pass your input through the transformer model, then you need to get the logits from the model.

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

MakerDiTy
TypeEmbedding models
Parameters (lead)178M
Context512 tokens
Variants1
Runs withsentence-transformers
Based onDeepPavlov/rubert-base-cased
Released2024-04-19
Popularity78k downloads / month
Likes29
LicenceOpen weights

How it works

How embedding models work

Your textsentence / documentEncodermaps meaningVectorlist of numbersAn embedding model turns text into a vector, so similar meanings sit close together — the basis of search and RAG.

Variants

Sizes & precisions

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.

VariantParamsPrecisionVRAMFits 16 GBWeights
cross-encoder-russian-msmarco178MBF16~0.4 GBWeights ↗

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys cross-encoder-russian-msmarco for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (cross-encoder-russian-msmarco 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":"cross-encoder-russian-msmarco","input":"text to embed"}'

Details

Languages, data & research

Languages

ru

Trained / evaluated on

unicamp-dl/mmarco

Tags

sentence-transformers safetensors bert text-classification transformers rubert cross-encoder reranker msmarco text-ranking ru dataset:unicamp-dl/mmarco text-embeddings-inference endpoints_compatible

Licence

Open weights

Open weights under mit — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗

Sources

Weights & code

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