20Kdl/month
27likes
Identifier
Model ID
cross-encoder/nli-distilroberta-baseTags
sentence-transformerspytorchjaxonnxsafetensorsopenvinorobertatext-classificationtransformerszero-shot-classificationendataset:nyu-mll/multi_nlidataset:stanfordnlp/snlibase_model:distilbert/distilroberta-basebase_model:quantized:distilbert/distilroberta-baselicense:apache-2.0deploy:azureregion:us
Use nli-distilroberta-base on Mixpeek
Build multimodal processing pipelines with this model and others. Extract features, run inference, and set up retrieval in Mixpeek Studio.
Open StudioHow It Runs on Mixpeek
On Mixpeek, nli-distilroberta-base runs as a managed extractor inside a processing pipeline. Point a bucket of zero shot classification data at it, and Mixpeek handles GPU provisioning, batching, retries, and writing the outputs into a vector store you can query.
Extractor outputs land in the Mixpeek Vector Store (MVS), where you can combine them with retrieval, reranking, and filter stages to build end-to-end search and agent-perception pipelines, no model-serving infrastructure to maintain.
Specification
Organizationcross-encoder
TaskZero Shot Classification
Librarysentence-transformers
Licenseapache-2.0
Downloads/mo20K
Likes27
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