alt.freeweights.vision / gliner_large-v2
From: urchade <huggingface.co/urchade>Newsgroups: alt.freeweights.visionSubject:

gliner_large-v2

Date: 2026-11-15Commit: 9d0533eSigned: 2DC28CC7B26A283B ✓

Token classification model with 459M parameters. Safetensors weights, 3.68 GB in all. Published by urchade under Apache-2.0.

459M params3.68GBgliner_large-v2safetensorspermissive
FactsParams459MSize3.68 GBFormatssafetensorsTasktoken classificationLicenseApache-2.0From sourcepermissive
$ fw get urchade/gliner_large-v2
# manifest sha256 f19e75ca6d89… · 3.68 GB · 5 files
$ fw verify ./gliner_large-v2 urchade/gliner_large-v2
From sourceHosted (signed)urchade/gliner_large-v2Last check: 2026-11-15 02:28 UTC

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

Works with

Runs with

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

Overview

Size
3.68 GB
Weights
1.84 GB (safetensors)
Parameters
459M
Formats
safetensors
Task
token classification
License
Apache-2.0 (permissive)
Files
5, each with a sha256
Publisher
urchade
Added
2026-11-15
Section
alt.freeweights.vision
Lineage

Original release from the publisher.

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 02:28 UTCpassed

Model card

From the publisher at commit 9d0533e. Shown as plain text with links; images open at the publisher.

Model Card for GLiNER-large-v2#

GLiNER is a Named Entity Recognition (NER) model capable of identifying any entity type using a bidirectional transformer encoder (BERT-like). It provides a practical alternative to traditional NER models, which are limited to predefined entities, and Large Language Models (LLMs) that, despite their flexibility, are costly and large for resource-constrained scenarios.

This version has been trained on the NuNER dataset (commercially permissive).

Available models#

| Release | Model Name | # of Parameters | Language | License |

| - | - | - | - | - |

| v0 | urchade/gliner_base urchade/gliner_multi | 209M 209M | English Multilingual | cc-by-nc-4.0 | | v1 | urchade/gliner_small-v1 urchade/gliner_medium-v1 urchade/gliner_large-v1 | 166M 209M 459M | English English English | cc-by-nc-4.0 | | v2 | urchade/gliner_small-v2 urchade/gliner_medium-v2 urchade/gliner_large-v2 | 166M 209M 459M | English English English | apache-2.0 | | v2.1 | urchade/gliner_small-v2.1 urchade/gliner_medium-v2.1 urchade/gliner_large-v2.1 urchade/gliner_multi-v2.1 | 166M 209M 459M 209M | English English English Multilingual | apache-2.0 |

Installation#

To use this model, you must install the GLiNER Python library:

!pip install gliner

Usage#

Once you've downloaded the GLiNER library, you can import the GLiNER class. You can then load this model using GLiNER.from_pretrained and predict entities with predict_entities.

from gliner import GLiNER

model = GLiNER.from_pretrained("urchade/gliner_largev2")

text = """
Cristiano Ronaldo dos Santos Aveiro (Portuguese pronunciation: [kɾiʃˈtjɐnu ʁɔˈnaldu]; born 5 February 1985) is a Portuguese professional footballer who plays as a forward for and captains both Saudi Pro League club Al Nassr and the Portugal national team. Widely regarded as one of the greatest players of all time, Ronaldo has won five Ballon d'Or awards,[note 3] a record three UEFA Men's Player of the Year Awards, and four European Golden Shoes, the most by a European player. He has won 33 trophies in his career, including seven league titles, five UEFA Champions Leagues, the UEFA European Championship and the UEFA Nations League. Ronaldo holds the records for most appearances (183), goals (140) and assists (42) in the Champions League, goals in the European Championship (14), international goals (128) and international appearances (205). He is one of the few players to have made over 1,200 professional career appearances, the most by an outfield player, and has scored over 850 official senior career goals for club and country, making him the top goalscorer of all time.
"""

labels = ["person", "award", "date", "competitions", "teams"]

entities = model.predict_entities(text, labels)

for entity in entities:
    print(entity["text"], "=>", entity["label"])
Cristiano Ronaldo dos Santos Aveiro => person
5 February 1985 => date
Al Nassr => teams
Portugal national team => teams
Ballon d'Or => award
UEFA Men's Player of the Year Awards => award
European Golden Shoes => award
UEFA Champions Leagues => competitions
UEFA European Championship => competitions
UEFA Nations League => competitions
Champions League => competitions
European Championship => competitions

Named Entity Recognition benchmark result#

Image: image/png

Model Authors#

The model authors are:

Files

5 files · 3.68 GBWeights 1.84 GB (safetensors). Sizes and sha256 from the signed manifest.
Hide all 5 files with their sha256
FileSizesha256
.gitattributes1.52 KB11ad7efa24975ee4b0c3c3a38ed18737f0658a5f75a0a96787b576a78a023361
README.md4.49 KBa0d6cec989b7e15995be6b2c807054c8805b9a579ac095325816936a683a2c40
gliner_config.json474 B8e88b694bcb0bfd4f93302951dd43d89261849c9817140681efc819a10472d9f
model.safetensors1.84 GB32ce07a1c5a41185c97047c42960dae98f33428295098dae1bd51cf401681054
pytorch_model.bin1.84 GB36bb03139034378b093de421ebc4a3052b7cfabbc089f4644d5be16d51aafc14
VersionsEach time the pinned upstream commit or file list changed in this repo. Newest first.
Upstream commitDateContents
9d0533ed97 pinned now2026-11-15 02:28 UTC5 files · 3.68 GB

Use it

$ fw get urchade/gliner_large-v2
# manifest sha256 f19e75ca6d89… · 3.68 GB · 5 files
$ fw verify ./gliner_large-v2 urchade/gliner_large-v2
fw.pyChecks the signature and every sha256, tries each source in order, resumes.
$ python3 fw.py get https://freeweights.allternit.com/manifests/urchade/gliner_large-v2.json --dir ./gliner_large-v2 $ python3 fw.py verify ./gliner_large-v2 ./urchade__gliner_large-v2.json
hfThe Hugging Face CLI with one setting. Same repo id.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download urchade/gliner_large-v2 --revision 9d0533ed97ade535f232b28dc673999c27c43159 --local-dir ./gliner_large-v2

License

Name
Apache License 2.0
Id
Apache-2.0
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
a0d6cec989b7e15995be6b2c807054c8805b9a579ac095325816936a683a2c40
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: urchade <huggingface.co/urchade>Newsgroups: alt.freeweights.visionSubject: gliner_large-v2Date: 2026-11-15Commit: 9d0533eSigned: 2DC28CC7B26A283B ✓
Upstream
urchade/gliner_large-v2
Pinned commit
9d0533ed97ade535f232b28dc673999c27c43159
Manifest
gliner_large-v2.json · .minisig
Manifest sha256
f19e75ca6d89ebdcdcba9d5ae5a5f0c7417cd065664810ad47bbd20bc0c30040
Signature
minisign, Ed25519, key 2DC28CC7B26A283B
Created
2026-11-15 02:28 UTC
Generator
freeweights-manifest/0.1.0
Takedowns
None.

How to verify

$ curl -O https://freeweights.allternit.com/manifests/urchade/gliner_large-v2.json $ curl -O https://freeweights.allternit.com/manifests/urchade/gliner_large-v2.json.minisig $ minisign -Vm gliner_large-v2.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

1 model in the catalog name this one as their parent.

Quantizations
1
Quantizations 1
Get it
Download
$ HF_ENDPOINT=https://freeweights.allternit.com hf download urchade/gliner_large-v2
Open in Freeweights Studio

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

Signed manifest
minisign, key 2DC28CC7B26A283B. gliner_large-v2.json. Provenance. Takedown history: none.

Variants

1 quantized or adapter build of gliner_large-v2. Each has its own license check and page.

From: dima806 <huggingface.co/dima806>Subject: ai_vs_real_image_detection
From: legekka <huggingface.co/legekka>Subject: AI-Anime-Image-Detector-ViT
From: onnx-community <huggingface.co/onnx-community>Subject: AI-Anime-Image-Detector-ViT-ONNX
From: AICodexLab <huggingface.co/AICodexLab>Subject: answerdotai-ModernBERT-base-ai-detector
From: onnx-community <huggingface.co/onnx-community>Subject: answerdotai-ModernBERT-base-ai-detector-ONNX
From: onnx-community <huggingface.co/onnx-community>Subject: bart-large-cnn-ONNX