gguf-Q8_0-all-MiniLM-L6-v2

Name: gguf-Q8_0-all-MiniLM-L6-v2
Author: Felladrin

by Felladrin

6Kdl/month

HuggingFace Run it on your own data, free

Identifier

Model ID

Felladrin/gguf-Q8_0-all-MiniLM-L6-v2

Tags

sentence-transformersgguffeature-extractionsentence-similaritytransformersllama-cppgguf-my-repoendataset:s2orcdataset:flax-sentence-embeddings/stackexchange_xmldataset:ms_marcodataset:gooaqdataset:yahoo_answers_topicsdataset:code_search_netdataset:search_qadataset:eli5dataset:snlidataset:multi_nlidataset:wikihowdataset:natural_questionsdataset:trivia_qadataset:embedding-data/sentence-compressiondataset:embedding-data/flickr30k-captionsdataset:embedding-data/altlexdataset:embedding-data/simple-wikidataset:embedding-data/QQPdataset:embedding-data/SPECTERdataset:embedding-data/PAQ_pairsdataset:embedding-data/WikiAnswersbase_model:sentence-transformers/all-MiniLM-L6-v2

Use gguf-Q8_0-all-MiniLM-L6-v2 on Mixpeek

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

Open Studio

How It Runs on Mixpeek

On Mixpeek, gguf-Q8_0-all-MiniLM-L6-v2 runs as a managed extractor inside a processing pipeline. Point a bucket of sentence similarity 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.