Model reference · open weights

specter

specter is an open-weight embedding model from allenai, 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 allenai 1 variants 23k downloads/mo
Request this model on EU hardware All served models Not on the shared API today — deployed on request.

About

What specter is

SPECTER SPECTER is a pre-trained language model to generate document-level embedding of documents. It is pre-trained on a powerful signal of document-level relatedness: the citation graph. Unlike existing pretrained language models, SPECTER can be easily applied to downstream applications without task-specific fine-tuning. If you're coming here because you want to embed papers, SPECTER has now been superceded by SPECTER2. Use that instead. Paper: SPECTER: Document-level Representation Learning using Citation-informed Transformers Original Repo: Github Evaluation Benchmark: SciDocs Authors: Arman Cohan, Sergey Feldman, Iz Beltagy, Doug Downey, Daniel S. Weld

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

Specifications

What it is

Makerallenai
TypeEmbedding models
Context512 tokens
Variants1
Runs withtransformers
Released2022-03-02
Popularity23k downloads / month
Likes65
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
specterBF16Weights ↗

Using it via the API

Call it like any OpenAI endpoint

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

Details

Languages, data & research

Languages

en

Trained / evaluated on

SciDocs

Tags

transformers pytorch tf jax bert feature-extraction en dataset:SciDocs endpoints_compatible deploy:azure

Papers

Licence

Open weights

Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗

Sources

Weights & code

Want specter on EU-owned hardware?

Request this model on EU hardware See what’s served now

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