Nepali_Embedding_Model
Can I run Nepali_Embedding_Model on my computer?
It depends on your memory, processor, file format and runtime. Hugging Bay offers 8 hosted files; check the file list for the exact selection. A file-size fit is an estimate, not a successful run or speed promise. Read the license before use.
Nepali_Embedding_Model is an embedding model for sentence similarity and retrieval. Model weights are learned parameters; a runtime loads them. A hosted file is an individual file Hugging Bay can serve. SHA-256 identifies exact file bytes. The availability date above applies to this file record, not the upstream metadata update date.
As of the recorded file availability check on .
Recorded SHA-256 for model.safetensors: 9896ca3aa5099620001a7eba78c5dbf064c5b531ca15184e4913f40ef1549cd0. Exact file evidence · Machine-readable source facts · Run evidence and any recorded receipts. A checksum fingerprints only the named file bytes; it does not prove safety, quality, a complete multi-file selection or a successful run.
Updated · Page-copy source revision 8871bab84e1cf80aea1686a944ec335078a6c036 · Source files: apps/web/lib/model-page-template.mjs, apps/web/lib/model-page-v3.mjs, apps/web/lib/aeo-page.mjs · Full revision record
Model metadata: As of at the model source. Popularity counters are source-reported, not measured by Hugging Bay. Availability checked .
universalml/Nepali_Embedding_ModelNo recent measured run
Fresh signed measurements are unavailable for this file.
Browse other models, or check this page again later for measured results.