MNLP_M3_document_encoder
pmdlt/MNLP_M3_document_encoderContent controls: not assessed.
Listed for turning text into vectors; for developers building text similarity tools. Metadata confidence: medium.
Informações do modelo
MNLP_M3_document_encoder is an embedding model for text embeddings. The primary file is model.safetensors (133 MB). The primary file needs about 2 GB free for the selected file. License: MIT. The SHA-256 prefix is ea1d11a3f23d. The primary Download is available now. No tested run commands for this file yet. See Files for current download availability. The size and hash details refer to the selected file, not every file in the repository. The memory figure is estimated from recorded file size with working room included. The size line uses recorded file bytes when they are present in this model record.
O que está incluído
8 hosted of 12 listed
Sobre este modelo
External Hugging Face catalog record for pmdlt/MNLP_M3_document_encoder. Task: feature extraction. Library: sentence transformers. Languages: en. Includes 12 model-card evaluation signals. Popularity signal at import: 79 downloads and 0 likes.
Informações básicas
- Hosted here
- 8 hosted of 12 listed
- Full repo upstream
- 134.5 MB
- Recommended file
- 133.5 MB · model.safetensors
- Languages
- en
- Format
- safetensors
- Downloads on Hugging Face
- 59
- File hashes
- Hashes recorded. Date not recorded.
Licença e origem
License: mit
Check the license text and keep the required notices when you use or share the files.
Upstream source →- Task
- text embeddings
- Hosted here
- at least 8 listed files; full count and size unknown
- Full repo upstream
- 134.5 MB
- Recommended file
- 133.5 MB · model.safetensors
- Files
- 8 hosted of 12 listed
- Download
- Download here (8 hosted files)
- Added to Hugging Bay
- Updated at source
FAQ
What is this model?
pmdlt/MNLP_M3_document_encoder is an embedding model for text embeddings published by pmdlt, added to Hugging Bay Jun 30, 2026. Model from Hugging Face for feature extraction: pmdlt/MNLP_M3_document_encoder · sentence transformers
Can I use it commercially?
It is released under the mit license. Commercial use is allowed. Permissive open license: commercial use, modification, and redistribution are permitted.
How big is it?
Hosted here: at least 8 listed files; full count and size unknown. Full repo upstream: 134.5 MB. The recommended download, model.safetensors, is 133.5 MB.
What can I download here?
Hosted here: at least 8 listed files; full count and size unknown. Full repo upstream: 134.5 MB. The original release is at https://huggingface.co/pmdlt/MNLP_M3_document_encoder.
File checks and computer fit
File pattern scans
Automated file-pattern scans flagged nothing; not a safety guarantee. 8 hosted files carry a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-pmdlt-mnlp-m3-document-encoder/safety on Hugging Bay.
Will pmdlt/MNLP_M3_document_encoder run on my computer?
We can’t check the fit; we don’t know your machine. We don’t have your machine’s specs, so no check ran and no verdict is shown. Answer two quick questions and we’ll estimate, from the memory you tell us, whether it fits your machine. Or skip it; you can still download; fit isn’t checked.