sciembed-ctx-8192 safetensors download | Hugging Bay

Q: What is this model?

anon-nlp/sciembed-ctx-8192 is an embedding model for text embeddings published by anon-nlp, added to Hugging Bay Jun 30, 2026. Model from Hugging Face: anon-nlp/sciembed-ctx-8192

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 10 listed files; full count and size unknown. The full repository size is not recorded. The recommended download, model.safetensors, is 596.1 MB.

Q: What can I download here?

Hosted here: at least 10 listed files; full count and size unknown. Full repo upstream: unknown. The original release is at https://huggingface.co/anon-nlp/sciembed-ctx-8192.

Q: File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 10 hosted files carry a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-anon-nlp-sciembed-ctx-8192/safety on Hugging Bay.

Q: Will anon-nlp/sciembed-ctx-8192 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.

anon-nlp

sciembed-ctx-8192

anon-nlp/sciembed-ctx-8192

Model details

text embeddingsLicense: mitSHA-256 recorded for 10 of 11 filessafetensors

Content controls: not assessed.

Listed for comparing sentences; for developers building text similarity tools. Catalog sources: license, tags, task.

View as JSON →

Your next step

Use it from code

This Python snippet downloads the selected file. Running the model needs its own library and setup.

from urllib.request import urlretrieve

urlretrieve(
    "https://huggingbay.xyz/api/downloads/hf-model-anon-nlp-sciembed-ctx-8192/model.safetensors",
    "model.safetensors",
)

Other ways

Run it on your computerOpen in Hugging Bay appSend to a computerApp links support one GGUF file.

10 hosted of 11 listed · Hashes recorded. Date not recorded.

Selected downloadmodel.safetensors596 MB · 1 file Download · 596 MB (1 file)

Open-file help

Content controls: not assessed.

Check your download →

Compare your file’s SHA-256 with the recorded hash.

10 hosted of 11 listed

Hashes recorded. Date not recorded.

File	आकार	SHA-256	स्रोत	डाउनलोड करें
Weights
`model.safetensors` Default	596.1 MB	`5ff0c089…a313b0ae` `5ff0c08975f6ad71363f1fcfa79af87dc4bc531d57e15f8b84fc91fba313b0ae`	Hosted	डाउनलोड करें
Tokenizer & config
`1_Pooling/config.json`	312 bytes	`35bbd47d…cc8ebcc6` `35bbd47d7fdf1e378db6130bcc668b09d1aa67a7bbf7c8f89a9c71f4cc8ebcc6`	Hosted	डाउनलोड करें
`config.json`	1.21 KB	`f295786e…0f70a9dd` `f295786e36cabd2023fd17bbf048f355926bb80a9ced63d22826f3310f70a9dd`	Hosted	डाउनलोड करें
`config_sentence_transformers.json`	283 bytes	`4e30d5e9…52e4ca66` `4e30d5e9800534a1d1511c69f7d29a0136604b7eec257a8290e552af52e4ca66`	Hosted	डाउनलोड करें
`modules.json`	229 bytes	`8f4b264b…b3145460` `8f4b264b80206c830bebbdcae377e137925650a433b689343a63bdc9b3145460`	Hosted	डाउनलोड करें
`sentence_bert_config.json`	58 bytes	`9ee39351…37e627b3` `9ee3935137f87c9ce6662ae17fe7afb7c9c64744a41247359fd228dc37e627b3`	Hosted	डाउनलोड करें
`special_tokens_map.json`	694 bytes	`ea97ecdb…1be81049` `ea97ecdbcc73713039d8d64dbb05e3689495c96657fbd9a18f5bed381be81049`	Hosted	डाउनलोड करें
`tokenizer_config.json`	20.8 KB	`2966a59b…28d4e560` `2966a59b9e9cf122279aec1249e22e5bc7ad8430c754e95031b13fd128d4e560`	Hosted	डाउनलोड करें
`tokenizer.json`	3.58 MB	`bb637767…f6ac543d` `bb637767e8dfb8044597df6c58243bff2e592ae9e3b310c0bbdb8591f6ac543d`	Hosted	डाउनलोड करें
Docs
`README.md`	1.22 KB	`e1cd6afc…4a0f33fc` `e1cd6afc544207ce49116cc334c1333b56164aa748f8652b744d3c1a4a0f33fc`	Hosted	डाउनलोड करें
`.gitattributes`	0 bytes	—	Upstream only	File metadata

डाउनलोड की जाँच करें

In the folder where you saved model.safetensors, run:

macOS

shasum -a 256 -- 'model.safetensors'

Linux

sha256sum -- 'model.safetensors'

Windows

Get-FileHash -LiteralPath 'model.safetensors' -Algorithm SHA256

Compare the result with the recorded SHA-256.

sciembed-ctx-8192

डाउनलोड की जाँच करें

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