roberta-base safetensors download (499 MB) | Hugging Bay

Q: What is this model?

deepvk/roberta-base is an embedding model for text embeddings published by deepvk, added to Hugging Bay Jun 30, 2026. Model from Hugging Face: deepvk/roberta-base

Q: Can I use it commercially?

It is released under the apache-2.0 license. Commercial use is allowed. Permissive open license: commercial use, modification, and redistribution are permitted.

Q: How big is it?

Hosted here: at least 9 listed files; full count and size unknown. The full repository size is not recorded. The recommended download, model.safetensors, is 498.6 MB.

Q: What can I download here?

Hosted here: at least 9 listed files; full count and size unknown. Full repo upstream: unknown. The original release is at https://huggingface.co/deepvk/roberta-base.

Q: File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 9 hosted files carry a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-deepvk-roberta-base/safety on Hugging Bay.

Q: Will deepvk/roberta-base 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.

deepvk

roberta-base

deepvk/roberta-base

Model details

text embeddingsLicense: apache-2.0SHA-256 recorded for 9 of 11 filessafetensors · BIN

Content controls: not assessed.

Listed for extracting features; for developers building feature extraction tools. Catalog sources: license, 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-deepvk-roberta-base/model.safetensors",
    "model.safetensors",
)

Other ways

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

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

Selected downloadmodel.safetensors499 MB · 1 file Download · 499 MB (1 file)

Open-file help

Content controls: not assessed.

Check your download →

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

9 hosted of 11 listed

Hashes recorded. Date not recorded.

File	आकार	SHA-256	स्रोत	डाउनलोड करें
Weights
`model.safetensors` Default	498.6 MB	`14a76e9b…05721688` `14a76e9bd8e0fc9dbfaa2eac0ae32c9bf4954112cf53a030c5a2ce9805721688`	Hosted	डाउनलोड करें
`pytorch_model.bin`	0 bytes	—	Upstream only	File metadata
Tokenizer & config
`added_tokens.json`	21 bytes	`0297d10e…d8617524` `0297d10e4fe6be78486f9a12dc2919fe2d0e73828d1e158db96e5448d8617524`	Hosted	डाउनलोड करें
`config.json`	677 bytes	`c41429b1…e6659bba` `c41429b187342541832b305f5da0616975c4e71845c76eab4228aaaee6659bba`	Hosted	डाउनलोड करें
`merges.txt`	1.31 MB	`f9eb78a3…2c4719bc` `f9eb78a342ebb7025624408244f5446ce5eeba5b0bc9db4816e787f22c4719bc`	Hosted	डाउनलोड करें
`tokenizer.json`	3.81 MB	`a5cb9468…edb6bb72` `a5cb94689a402eb403bbe04de8c51dea16590dde51fa35f2727e6a0fedb6bb72`	Hosted	डाउनलोड करें
`tokenizer_config.json`	1.35 KB	`1e18c122…c4b2a446` `1e18c1220e013cf5d2593a72b6053d9c2fdea67d75ad766915c9cbecc4b2a446`	Hosted	डाउनलोड करें
`vocab.json`	1.65 MB	`786b4b3b…e0f61abc` `786b4b3b4945929df17f1f64bded210f4df8d8d6b691eee59d94900fe0f61abc`	Hosted	डाउनलोड करें
`special_tokens_map.json`	957 bytes	`8293ae96…2eb2d4b7` `8293ae960b0a0852d4d3813118030a1149a3ed9fe37bc2e1e7b3c2e62eb2d4b7`	Hosted	डाउनलोड करें
Docs
`README.md`	3.55 KB	`4e2bba12…882e2d21` `4e2bba12fd6563e9bdd17906306044dae58c7775aa3bf30ec7a92e39882e2d21`	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.

roberta-base

डाउनलोड की जाँच करें

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