llama-3-finetuned-for-subjectivity-english-lora
by ashrafulparan
21dl/month
1likes
Identifier
Model ID
ashrafulparan/llama-3-finetuned-for-subjectivity-english-loraTags
peftsafetensorssubjectiviyzero-shot-classificationenbase_model:unsloth/llama-3-8b-bnb-4bitbase_model:adapter:unsloth/llama-3-8b-bnb-4bitlicense:apache-2.0region:us
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Open StudioHow It Runs on Mixpeek
On Mixpeek, llama-3-finetuned-for-subjectivity-english-lora 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
Organizationashrafulparan
TaskZero Shot Classification
Librarypeft
Licenseapache-2.0
Downloads/mo21
Likes1
View on HuggingFace
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