splade-camembert-base-v2 safetensors download | Hugging Bay

Q: What is this model?

sparse-encoder/splade-camembert-base-v2 is an embedding model for text embeddings published by sparse-encoder, added to Hugging Bay Sep 22, 2026. Model from Hugging Face for feature extraction: sparse-encoder/splade-camembert-base-v2 · sentence transformers

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: 8 files, 445.1 MB. Full repo upstream: 445.4 MB. The recommended download, model.safetensors, is 442.6 MB.

Q: What can I download here?

Hosted here: 8 files, 445.1 MB. Full repo upstream: 445.4 MB. The original release is at https://huggingface.co/sparse-encoder/splade-camembert-base-v2.

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-sparse-encoder-splade-camembert-base-v2/safety on Hugging Bay.

Q: Will sparse-encoder/splade-camembert-base-v2 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.

sparse-encoder

splade-camembert-base-v2

sparse-encoder/splade-camembert-base-v2

Model details

text embeddingsLicense: apache-2.0SHA-256 recorded for 8 of 11 filessafetensors

Content controls: not assessed.

Listed for turning text into vectors; for developers building text similarity tools. Catalog sources: license, cardMetadata.license, baseModel, cardMetadata.libraryName, modality, task, cardMetadata.pipelineTag.

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-sparse-encoder-splade-camembert-base-v2/model.safetensors",
    "model.safetensors",
)

Other ways

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

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

Selected downloadmodel.safetensors443 MB · 1 file Download · 443 MB (1 file)

Open-file help

Content controls: not assessed.

Check your download →

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

8 hosted of 11 listed

Hashes recorded. Date not recorded.

File	Tamaño	SHA-256	Origen	Descargar
Weights
`model.safetensors` Default	442.6 MB	`aef2cd38…fb8cb58a` `aef2cd382cb34fcc069a15957e39819bc3c674294908baf77b53cab5fb8cb58a`	Hosted	Descargar
Tokenizer & config
`1_SpladePooling/config.json`	107 bytes	—	Upstream only	File metadata
`config.json`	664 bytes	`9ae6044a…460ecfa0` `9ae6044adc1d97650103e50bf2758ae5d44a277829d12a31b940d128460ecfa0`	Hosted	Descargar
`config_sentence_transformers.json`	279 bytes	`dab6f16c…59964870` `dab6f16c0a8a82a66b899212d9179af9699752c89b9aa4e140c8924d59964870`	Hosted	Descargar
`modules.json`	274 bytes	`49d17c58…2479e1e3` `49d17c5888db1d0f18dde2855770b5f796240df89ddf56f8589380072479e1e3`	Hosted	Descargar
`sentence_bert_config.json`	57 bytes	`948201d8…ee986529` `948201d8329907aae938fa62f9ceeed53f5694dacc2b87b9f3b78b37ee986529`	Hosted	Descargar
`special_tokens_map.json`	374 bytes	`b547935b…8545e225` `b547935baa93c5a14e68b1dc220a11c840bec3b75dc9cf11b75b551a8545e225`	Hosted	Descargar
`tokenizer.json`	2.42 MB	`e7010641…e3e79527` `e70106411ce80dafb4401a61713eb952cf5cf635f18776a1bd32b8f6e3e79527`	Hosted	Descargar
`tokenizer_config.json`	1.79 KB	`bde6934e…e4fc1177` `bde6934e2625751ec86ceacca216e0184f960a5b29691a2420dff1e4e4fc1177`	Hosted	Descargar
Docs
`.gitattributes`	1.52 KB	—	Upstream only	File metadata
`README.md`	337.5 KB	—	Upstream only	File metadata

Comprobar una descarga

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.

splade-camembert-base-v2

Comprobar una descarga

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