MNLP_M2_document_encoder safetensors download | Hugging Bay

Q: What is this model?

arnaultsta/MNLP_M2_document_encoder is an embedding model for text embeddings published by arnaultsta, added to Hugging Bay Jun 30, 2026. Model from Hugging Face for feature extraction: arnaultsta/MNLP_M2_document_encoder · sentence transformers

Q: 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.

Q: How big is it?

Hosted here: at least 8 listed files; full count and size unknown. Full repo upstream: 401.1 MB. The recommended download, model.safetensors, is 133.5 MB.

Q: What can I download here?

Hosted here: at least 8 listed files; full count and size unknown. Full repo upstream: 401.1 MB. The original release is at https://huggingface.co/arnaultsta/MNLP_M2_document_encoder.

Q: 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-arnaultsta-mnlp-m2-document-encoder/safety on Hugging Bay.

Q: Will arnaultsta/MNLP_M2_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.

arnaultsta

MNLP_M2_document_encoder

arnaultsta/MNLP_M2_document_encoder

text embeddingsLicense: mitHashes recordedsafetensors · ONNX · BIN

Content controls: not assessed.

Model from Hugging Face for feature extraction: arnaultsta/MNLP_M2_document_encoder · sentence transformers

View as JSON →

8 hosted of 14 listed

Hashes recorded. Date not recorded.

File	Size	SHA-256	Source	Download
Weights
`model.safetensors` Default	133.5 MB	`3c9f3166…317e21ad` `3c9f31665447c8911517620762200d2245a2518d6e7208acc78cd9db317e21ad`	Hosted	Download
`onnx/model.onnx`	133.1 MB	`828e1496…9940cf35` `828e1496d7fabb79cfa4dcd84fa38625c0d3d21da474a00f08db0f559940cf35`	Upstream only	File metadata
`pytorch_model.bin`	133.5 MB	`84868a67…31728b88` `84868a67d847f7f37d1df745b73a4c20b5bc0a797c87a23b265f8a0131728b88`	Upstream only	File metadata
Tokenizer & config
`1_Pooling/config.json`	190 bytes	—	Upstream only	File metadata
`config.json`	743 bytes	`094f8e89…f3084750` `094f8e891b932f2000c92cfc663bac4c62069f5d8af5b5278c4306aef3084750`	Hosted	Download
`config_sentence_transformers.json`	124 bytes	`940d5f50…8bdd7c56` `940d5f50db195fa6e5e6a4f122c095f77880de259d74b14a65779ed48bdd7c56`	Hosted	Download
`sentence_bert_config.json`	52 bytes	`84e39fda…2a693cbf` `84e39fda68ccbff05bfa723ae9c0e70e23e2ec373b76e0f8c6e71af72a693cbf`	Hosted	Download
`special_tokens_map.json`	125 bytes	`b6d346be…76237ee3` `b6d346be366a7d1d48332dbc9fdf3bf8960b5d879522b7799ddba59e76237ee3`	Hosted	Download
`tokenizer.json`	711.4 KB	`d241a60d…1f9e5c66` `d241a60d5e8f04cc1b2b3e9ef7a4921b27bf526d9f6050ab90f9267a1f9e5c66`	Hosted	Download
`tokenizer_config.json`	366 bytes	`9261e7d7…76172ab3` `9261e7d79b44c8195c1cada2b453e55b00aeb81e907a6664974b4d7776172ab3`	Hosted	Download
`vocab.txt`	231.5 KB	—	Upstream only	File metadata
`modules.json`	349 bytes	`84e40c8e…7cf642cf` `84e40c8e006c9b1d6c122e02cba9b02458120b5fb0c87b746c41e0207cf642cf`	Hosted	Download
Docs
`.gitattributes`	1.52 KB	—	Upstream only	File metadata
`README.md`	94.8 KB	—	Upstream only	File metadata

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MNLP_M2_document_encoder

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