alt.freeweights.embed / bge-base-en-v1.5-ONNX
From: onnx-community <huggingface.co/onnx-community>Newsgroups: alt.freeweights.embedSubject:

bge-base-en-v1.5-ONNX

Date: 2026-11-15Commit: e86c644Signed: 2DC28CC7B26A283B ✓

Feature extraction model. Onnx weights, 899 MB in all. Published by onnx-community under MIT.

embed899MBbge-base-en-v1.5-ONNXonnxpermissive
FactsParamsnot statedSize899 MBFormatsonnxTaskfeature extractionLicenseMITFrom sourcepermissive
$ fw get onnx-community/bge-base-en-v1.5-ONNX
# manifest sha256 6bbc509e8c16… · 899 MB · 15 files
$ fw verify ./bge-base-en-v1.5-ONNX onnx-community/bge-base-en-v1.5-ONNX
From sourceHosted (signed)onnx-community/bge-base-en-v1.5-ONNXLast check: 2026-11-15 05:29 UTC

Get help: custom fine-tune or private deploy. We review your setup before we quote.

Quantized of bge-base-en-v1.5.

Works with

Runs with

Ranked by fit to this model (onnx), then by GitHub stars.

Convert with

Evaluate with

Scan with

Overview

Size
899 MB
Weights
95.8 MB (smallest of 4 ONNX variants)
Parameters
not stated
Formats
onnx
Task
feature extraction
License
MIT (permissive)
Files
15, each with a sha256
Publisher
onnx-community
Added
2026-11-15
Section
alt.freeweights.embed
Lineage

Original release from the publisher.

Base model: BAAI/bge-base-en-v1.5

Where these bytes come from
Publisher at the pinned commit→You

Sources are tried in order. A file counts only when its size and sha256 match the manifest. Sources are checked when you ask for them, not on a timer.

Sources
BadgeHostLast checkResult
From sourcehuggingface.co2026-11-15 05:29 UTCpassed

Model card

From the publisher at commit e86c644. Shown as plain text with links; images open at the publisher.

Usage (Transformers.js)#

If you haven't already, you can install the Transformers.js JavaScript library from NPM using:

npm i @huggingface/transformers

You can then use the model to compute embeddings, as follows:

import { pipeline } from '@huggingface/transformers';

// Create a feature-extraction pipeline
const extractor = await pipeline('feature-extraction', 'onnx-community/bge-base-en-v1.5-ONNX');

// Compute sentence embeddings
const texts = ['Hello world.', 'Example sentence.'];
const embeddings = await extractor(texts, { pooling: 'mean', normalize: true });
console.log(embeddings);
// Tensor {
//   dims: [ 2, 768 ],
//   type: 'float32',
//   data: Float32Array(1536) [ 0.019079938530921936, 0.041718777269124985, ... ],
//   size: 1536
// }

console.log(embeddings.tolist()); // Convert embeddings to a JavaScript list
// [
//   [ 0.019079938530921936, 0.041718777269124985, 0.037672195583581924, ... ],
//   [ 0.020936904475092888, 0.020080938935279846, -0.00787576474249363, ... ]
// ]

You can also use the model for retrieval. For example:

import { pipeline, cos_sim } from '@huggingface/transformers';

// Create a feature-extraction pipeline
const extractor = await pipeline('feature-extraction', 'onnx-community/bge-base-en-v1.5-ONNX');

// List of documents you want to embed
const texts = [
    'Hello world.',
    'The giant panda (Ailuropoda melanoleuca), sometimes called a panda bear or simply panda, is a bear species endemic to China.',
    'I love pandas so much!',
];

// Compute sentence embeddings
const embeddings = await extractor(texts, { pooling: 'mean', normalize: true });

// Prepend recommended query instruction for retrieval.
const query_prefix = 'Represent this sentence for searching relevant passages: '
const query = query_prefix + 'What is a panda?';
const query_embeddings = await extractor(query, { pooling: 'mean', normalize: true });

// Sort by cosine similarity score
const scores = embeddings.tolist().map(
    (embedding, i) => ({
        id: i,
        score: cos_sim(query_embeddings.data, embedding),
        text: texts[i],
    })
).sort((a, b) => b.score - a.score);
console.log(scores);
// [
//   { id: 1, score: 0.7787772374597298, text: 'The giant panda (Ailuropoda melanoleuca), sometimes called a panda bear or simply panda, is a bear species endemic to China.' },
//   { id: 2, score: 0.7071589521880506, text: 'I love pandas so much!' },
//   { id: 0, score: 0.4252782730390429, text: 'Hello world.' }
// ]

Files

15 files · 899 MBWeights 95.8 MB (smallest of 4 ONNX variants). Sizes and sha256 from the signed manifest.
Hide all 15 files with their sha256
FileSizesha256
.gitattributes1.76 KB5eb33170d4b83c5e7fd73cdeb7dcdb950fdb12d06d57352985243b7f18bff526
README.md2.80 KB728950fdc324ba0bb61255ab19955111cc3e842df3186f5a1a0707705f419970
config.json901 Baa88e76008f9eedff241aa9c980492adbf85fb281070fcc88a284fdd27d42643
onnx/model.onnx105 KBf910ee38fec73efe8e67973b071307f74cf4eec31c312b0fff6ca4ec22c96678
onnx/model.onnx_data436 MBf5560066d77fc4352a18344e0bc488d4f2c52f331f70547d3959df5465cd9e50
onnx/model_fp16.onnx106 KB8d171152c9f2c532f50fb030e9c0b59a0b65518f6897894dfad14de71d315461
onnx/model_fp16.onnx_data218 MB278fa12d66631e4d03ac96909576feaf2132cb26404a7ad50668c3b227bd7280
onnx/model_q4.onnx131 KB154591fb24f2029b9d962d03d2123a220355e1039b43bd5e6b8a85e7cb6b6f97
onnx/model_q4.onnx_data149 MB451f1abe191c64909eb18b0b76bed06cbfd4c157d76b37e673afbb96a89ea971
onnx/model_q4f16.onnx132 KBcf4b087298e5f18b12a0a4d48bf2977686485ccf89578012ffe680c1599e32a9
onnx/model_q4f16.onnx_data95.7 MB59c1b0ca651cf9be3ec44c6f6d20244933aef4c585e54f59f9d91ebf73b19b3c
special_tokens_map.json695 B5d5b662e421ea9fac075174bb0688ee0d9431699900b90662acd44b2a350503a
tokenizer.json534 KBea77de727ef7fd34d177b83b4b1f1d3bb8884c95c90b6554a0adb0b3b65350a9
tokenizer_config.json1.27 KBeebe14d184cfbd65f6a11d2a5ff39385c4044c8a670a89acf1a13331e04faa60
vocab.txt232 KB07eced375cec144d27c900241f3e339478dec958f92fddbc551f295c992038a3
VersionsEach time the pinned upstream commit or file list changed in this repo. Newest first.
Upstream commitDateContents
e86c6448e9 pinned now2026-11-15 05:29 UTC15 files · 899 MB

Use it

$ fw get onnx-community/bge-base-en-v1.5-ONNX
# manifest sha256 6bbc509e8c16… · 899 MB · 15 files
$ fw verify ./bge-base-en-v1.5-ONNX onnx-community/bge-base-en-v1.5-ONNX
fw.pyChecks the signature and every sha256, tries each source in order, resumes.
$ python3 fw.py get https://freeweights.allternit.com/manifests/onnx-community/bge-base-en-v1.5-ONNX.json --dir ./bge-base-en-v1.5-ONNX $ python3 fw.py verify ./bge-base-en-v1.5-ONNX ./onnx-community__bge-base-en-v1.5-ONNX.json
hfThe Hugging Face CLI with one setting. Same repo id.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download onnx-community/bge-base-en-v1.5-ONNX --revision e86c6448e9369e10a5a4e21dab5111e51672a617 --local-dir ./bge-base-en-v1.5-ONNX

License

Name
MIT License
Id
MIT
Class
Permissive
Redistribution
yes
Listing
Hosted (signed)
Decided
License as declared by the publisher. No person read it. 2026-11-15
Text in
README.md
Text sha256
728950fdc324ba0bb61255ab19955111cc3e842df3186f5a1a0707705f419970
Terms gate
No extra terms beyond the license.

Read the license text

Licenses are checked against the license table. A custom license passes only after a person reads it.

Provenance

From: onnx-community <huggingface.co/onnx-community>Newsgroups: alt.freeweights.embedSubject: bge-base-en-v1.5-ONNXDate: 2026-11-15Commit: e86c644Signed: 2DC28CC7B26A283B ✓
Upstream
onnx-community/bge-base-en-v1.5-ONNX
Pinned commit
e86c6448e9369e10a5a4e21dab5111e51672a617
Manifest
bge-base-en-v1.5-ONNX.json · .minisig
Manifest sha256
6bbc509e8c1644844f9a62057ad24df3429cbddae5162d438206236142c8552a
Signature
minisign, Ed25519, key 2DC28CC7B26A283B
Created
2026-11-15 05:29 UTC
Generator
freeweights-manifest/0.1.0
Takedowns
None.

How to verify

$ curl -O https://freeweights.allternit.com/manifests/onnx-community/bge-base-en-v1.5-ONNX.json $ curl -O https://freeweights.allternit.com/manifests/onnx-community/bge-base-en-v1.5-ONNX.json.minisig $ minisign -Vm bge-base-en-v1.5-ONNX.json -P RWQ7KGqyx4zCLXtUFOqvfv8L3g+8fpKJ1FsuxPyOYMF+4KufbUxKq1Oq $ shasum -a 256 <file> # compare with the Files tab

A manifest whose signature fails must be rejected. A file whose size or sha256 does not match must be discarded. Verify a download

Model tree

Parent

BAAI/bge-base-en-v1.5 · this model is a quantization of it

No model in the catalog names this one as its parent.

Get it
Download
$ HF_ENDPOINT=https://freeweights.allternit.com hf download onnx-community/bge-base-en-v1.5-ONNX
Open in Freeweights Studio

Pull, verify and run it in the Allternit app on Desktop, web or phone.

Signed manifest
minisign, key 2DC28CC7B26A283B. bge-base-en-v1.5-ONNX.json. Provenance. Takedown history: none.
From: sentence-transformers <huggingface.co/sentence-transformers>Subject: all-MiniLM-L6-v1
From: unsloth <huggingface.co/unsloth>Subject: all-MiniLM-L6-v2
From: mlx-community <huggingface.co/mlx-community>Subject: all-MiniLM-L6-v2-4bit
From: sentence-transformers <huggingface.co/sentence-transformers>Subject: all-mpnet-base-v1
From: sentence-transformers <huggingface.co/sentence-transformers>Subject: allenai-specter
From: sentence-transformers <huggingface.co/sentence-transformers>Subject: bert-base-nli-max-tokens