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Open-weight model

slopblock-modernbert-base

by Dang salmonfamin/slopblock-modernbert-base

slopblock-modernbert-base is an open-weight model from Dang. It has 8,192-token context. Its published files total 154.2 MB.

Parameters—
Context8,192
Weights150.6 MB
License—
AccessOpen weights
Monthly Downloads—

Model Card

The publisher has not written a card for this model.

Configuration

Architecture
ModernBertForSequenceClassification
Context length (tokens)
8,192
Layers
22
Hidden size
768
Feed-forward size
1,152
Attention heads
12
Vocabulary size
50,368
Stored precision
float32
Model type
modernbert

Identity and Version

Repository
salmonfamin/slopblock-modernbert-base
Publisher
Dang
Task
Not stated by the source
Modality
Other
Library
Not stated by the source
Parameters
Not stated by the source
Languages
Not stated by the source
Revision
72cb69dba0ec667301f314861589f4f034c9e843
First published
2026-09-24
Last updated
2026-09-24

Files and Weights

10 files, 154.2 MB in total. The weights are 1 file totalling 150.6 MB in onnx.

Weights1 file · 150.6 MB
Configuration6 files · 17.5 KB
Tokenizer2 files · 3.6 MB
Repository1 file · 1.5 KB
Every file
FileTypeSizeSHA-256
onnx/model_quantized.onnxWeights150.6 MB edfd8f378b33
browser_results.jsonConfiguration1.9 KB —
config.jsonConfiguration1.4 KB —
extension_test_results.jsonConfiguration4.1 KB —
metrics.jsonConfiguration8.1 KB —
onnx/config.jsonConfiguration1.4 KB —
special_tokens_map.jsonConfiguration694 B —
.gitattributesRepository1.5 KB —
tokenizer.jsonTokenizer3.6 MB —
tokenizer_config.jsonTokenizer20.8 KB —

License and Download

License
Not stated by the source
Access
Open weights, no gate
Download size
150.6 MB
Download from Dang

Released by Dang through its official repository on Hugging Face.

Memory Requirements

PrecisionWeights in memory
As published150.6 MB

Weights only, from the published parameter count; the key-value cache and runtime add to this.

Questions About slopblock-modernbert-base

What is slopblock-modernbert-base's context length?

8,192 tokens, from the maximum position embeddings in its published configuration.