NEWMVS for embeddings. Managed for files. Both on object storage.Vectors or files. Pick a path.Start →

Start here

Vector Store (MVS)

Bring your own vectors. Dense, sparse, and BM25 search on object storage.

Managed Indexing

Connect a bucket and auto-extract scenes, faces, OCR, transcripts, and embeddings.

Build

Compose multi-stage search in <100ms: filter, join, rerank.

Feature Extractors

Typed pipelines for faces, scenes, transcripts, OCR, fingerprints.

S3, GCS, R2, Mux, LangChain, MCP, and more. Connect your stack.

Generate and store embeddings from 50+ models, then search them.

By Industry

Talent search, brand safety, creative analytics.

Scene search, recommendation, archive access.

Visual search, PDP enrichment, catalog QA.

Lecture search, transcript Q&A, content safety.

View all solutions →

By Use Case

Face & Person Search

Find anyone across video libraries in milliseconds.

IP & Copyright Detection

Logos, songs, faces: one pipeline, one report.

Visual Taste & Recs

Scene-similarity ranked recommendations with RL.

Brand & Ad Safety

Pre-publish content screening at bid-time speeds.

View all use cases →

Build

API reference, SDKs, recipes, and architecture guides.

Launches, deep dives, and field notes from our engineers.

Browse supported HuggingFace models by task and modality.

See what teams are building with Mixpeek.

Education

Multimodal University

Fundamentals of multimodal retrieval, modules + certs.

Every term you need: embeddings to re-rankers.

Talks, demos, and customer sessions on demand.

Mixpeek vs. Pinecone, Weaviate, Twelve Labs, more.

Mission, team, and the multimodal vision.

We're hiring across research, infra, and design.

Talk to sales, support, or press.

White-glove 30-day production pilot for new customers.

Sign in Request Demo Start free →

Models/Table Question Answering/vaishali/HiTQA-M2M

Table Question Answeringmit

HiTQA-M2M

by vaishali

5dl/month

HuggingFace Use in Pipeline

Identifier

Model ID

vaishali/HiTQA-M2M

Tags

pytorchsafetensorsm2m_100lowrestabqalow-resource-table-question-answeringindic-table-question-answeringhindi-table-question-answeringtable-question-answeringhidataset:vaishali/hindiTabQAlicense:mitregion:us

Use HiTQA-M2M on Mixpeek

Build multimodal processing pipelines with this model and others. Extract features, run inference, and set up retrieval in Mixpeek Studio.

Specification

Organizationvaishali

TaskTable Question Answering

Licensemit

Downloads/mo5

View on HuggingFace

See model card, files, and community discussion

Related Table Question Answering Models

microsoft/tapex-base-finetuned-wikisql

google/tapas-large-finetuned-sqa

google/tapas-large-finetuned-wtq

google/tapas-base-finetuned-wtq

google/tapas-tiny-finetuned-sqa

lysandre/tiny-tapas-random-wtq

lysandre/tiny-tapas-random-sqa

google/tapas-base-finetuned-sqa