E5-Mistral-7B-Instruct-Embedding-GGUF download | Hugging Bay

Q: What is this model?

second-state/E5-Mistral-7B-Instruct-Embedding-GGUF is an embedding model for text embeddings published by second-state, added to Hugging Bay Jun 30, 2026. Model from Hugging Face for feature extraction: second-state/E5-Mistral-7B-Instruct-Embedding-GGUF · 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?

second-state/E5-Mistral-7B-Instruct-Embedding-GGUF has 7B parameters. Hosted here: 1 file, 4.37 GB. Full repo upstream: 69.1 GB. The recommended download, e5-mistral-7b-instruct-Q4_K_M.gguf (Q4_K_M), is 4.37 GB.

Q: What can I download here?

Hosted here: 1 file, 4.37 GB. Full repo upstream: 69.1 GB. The original release is at https://huggingface.co/second-state/E5-Mistral-7B-Instruct-Embedding-GGUF.

Q: File pattern scans

Automated file-pattern scans flagged nothing; not a safety guarantee. 1 hosted file carries a published SHA-256 you can re-hash. The machine-readable verdict is at /api/artifacts/hf-model-second-state-e5-mistral-7b-instruct-embedding-gguf/safety on Hugging Bay.

Q: Will second-state/E5-Mistral-7B-Instruct-Embedding-GGUF 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.

second-state

E5-Mistral-7B-Instruct-Embedding-GGUF

second-state/E5-Mistral-7B-Instruct-Embedding-GGUF

Model details

text embeddingsLicense: mitSHA-256 recorded for 13 of 16 filesGGUF

Content controls: not assessed.

The catalog lists this model for finding useful details in data. Catalog sources: license, cardMetadata.license, baseModel, task, cardMetadata.pipelineTag.

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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-second-state-e5-mistral-7b-instruct-embedding-gguf/e5-mistral-7b-instruct-Q4_K_M.gguf",
    "e5-mistral-7b-instruct-Q4_K_M.gguf",
)

Other ways

Run it on your computerOpen in Hugging Bay appSend to a computerMac (Apple silicon) and Linux x86_64 installs are listed on the download page. Windows and Intel Mac are not yet. The app checks this model before you choose to download.

1 hosted of 16 listed · Hashes recorded. Date not recorded.

Selected downloade5-mistral-7b-instruct-Q4_K_M.gguf4.37 GB · 1 file Download · 4.37 GB (1 file)

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Check your download →

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

1 hosted of 16 listed

Hashes recorded. Date not recorded.

File	Tamanho	SHA-256	Origem	Baixar
Weights
`e5-mistral-7b-instruct-Q4_K_M.gguf` Default	4.37 GB	`96f5b830…495ab5e4` `96f5b8305d2091b48dc1191c082e61cca1f0fc7181650106bed3dd5a495ab5e4`	Hosted	Baixar
`e5-mistral-7b-instruct-Q2_K.gguf`	2.72 GB	`f3de8028…81623bdd` `f3de8028cf73de436e3b7469d326e082b8f4bbfaa3a78482cce7f50c81623bdd`	Upstream only	File metadata
`e5-mistral-7b-instruct-Q3_K_L.gguf`	3.82 GB	`d885afa6…a70157df` `d885afa61abd5ba076420caf37773ce858803ad8cdd83e7ef908c7eda70157df`	Upstream only	File metadata
`e5-mistral-7b-instruct-Q3_K_M.gguf`	3.52 GB	`b3f601d9…5e04c4d6` `b3f601d9fbfe171b30d91662cbdd12afce505594c2a2b3ac2dff1af95e04c4d6`	Upstream only	File metadata
`e5-mistral-7b-instruct-Q3_K_S.gguf`	3.16 GB	`fc0a283d…14dad7bc` `fc0a283d2c6a2f4da84faea44b54923f1870f9c072f8449bbd9e4d5f14dad7bc`	Upstream only	File metadata
`e5-mistral-7b-instruct-Q4_0.gguf`	4.11 GB	`f75c0e30…0b5e3e89` `f75c0e30696fa7f1656320905943fb42e489e7c4156c37f37e9a17060b5e3e89`	Upstream only	File metadata
`e5-mistral-7b-instruct-Q4_K_S.gguf`	4.14 GB	`936c68fc…11355629` `936c68fccd86093be69cfc22c0a7bbee50b1ec9f6712fc2ab62cfcbd11355629`	Upstream only	File metadata
`e5-mistral-7b-instruct-Q5_0.gguf`	5 GB	`390dd181…3f3ed218` `390dd1811b1555fdf790a14a26d73db7b4b703b2d3104b7e40eb6c783f3ed218`	Upstream only	File metadata
`e5-mistral-7b-instruct-Q5_K_M.gguf`	5.13 GB	`606d2221…43409faf` `606d222135473106ac45139cc4f2582ad3065a3344a81e18e113e70043409faf`	Upstream only	File metadata
`e5-mistral-7b-instruct-Q5_K_S.gguf`	5 GB	`de884c70…a90282ce` `de884c70ce387a6886ef33b83a163e5451d05c058c846eda4e7982e1a90282ce`	Upstream only	File metadata
`e5-mistral-7b-instruct-Q6_K.gguf`	5.94 GB	`a93b1c51…ca625946` `a93b1c51cfe65192858dd4fc02eab38ab9616f4843f5a38c1db9371cca625946`	Upstream only	File metadata
`e5-mistral-7b-instruct-Q8_0.gguf`	7.7 GB	`16566015…2469bc23` `165660156014e0e4779b194d200d24ff7e47805eea27b0198283f7892469bc23`	Upstream only	File metadata
`e5-mistral-7b-instruct-f16.gguf`	14.5 GB	`b21f7dcb…a5f63ba3` `b21f7dcb5718c536b04d4463f4c1907d45dafc35308505e587f71019a5f63ba3`	Upstream only	File metadata
Tokenizer & config
`config.json`	629 bytes	—	Upstream only	File metadata
Docs
`.gitattributes`	1.56 KB	—	Upstream only	File metadata
`README.md`	4.2 KB	—	Upstream only	File metadata

Verificar um download

In the folder where you saved e5-mistral-7b-instruct-Q4_K_M.gguf, run:

macOS

shasum -a 256 -- 'e5-mistral-7b-instruct-Q4_K_M.gguf'

Linux

sha256sum -- 'e5-mistral-7b-instruct-Q4_K_M.gguf'

Windows

Get-FileHash -LiteralPath 'e5-mistral-7b-instruct-Q4_K_M.gguf' -Algorithm SHA256

Compare the result with the recorded SHA-256.

E5-Mistral-7B-Instruct-Embedding-GGUF

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