This model is a conversion of MoritzLaurer/roberta-base-zeroshot-v2.0-c to ONNX format using the Optimum library.
malkuth-2b is an open-weight model for zero-shot classification from Sae Chan O, released under Creative Commons Attribution-NonCommercial 4.0. Its published files total 91.5 MB.
A small multilingual decision model for classification, with a focus on Korean. Given a text, a question, and a set of criteria, Malkuth returns probabilities over the possible choices instead of generating text.
Parameters—
Context—
Weights71.5 MB
Licensecc-by-nc-4.0
AccessOpen weights
Monthly Downloads—
Model Card
A small multilingual decision model for classification, with a focus on Korean. Given a text, a question, and a set of criteria, Malkuth returns probabilities over the possible choices instead of generating text. Malkuth-2B is a LoRA adapter trained on Kev and built on a frozen empero-ai/Qwen3.8-2B-Distill. It has 17.9M trainable parameters and a 65 MB adapter. - choice: select one of up to 255 options - noul: yes or no - score: select an ordered level Multiple questions can be evaluated against the same input. Questions are evaluated independently, so they cannot see each other's answers. Probabilities are temperature-calibrated on a held-out validation split. Malkuth is served through Kev…
Excerpt from the card by Sae Chan O, licensed cc-by-nc-4.0.
Identity and Version
- Repository
- dhtocks/malkuth-2b
- Publisher
- Sae Chan O
- Task
- Zero-shot classification
- Modality
- Text
- Library
- peft
- Parameters
- Not stated by the source
- Languages
- en, ko, ja, zh, de, fr, es, hi
- Revision
- 37ae1672eebcf9ee5417418bd0be49f2e53d9087
- First published
- 2026-09-24
- Last updated
- 2026-09-25
Files and Weights
10 files, 91.5 MB in total. The weights are 2 files totalling 71.5 MB in pt, safetensors.
Weights2 files · 71.5 MB
Configuration3 files · 3.2 KB
Tokenizer2 files · 20.0 MB
Documentation1 file · 4.9 KB
Other1 file · 7.8 KB
Repository1 file · 1.6 KB
Every file
| File | Type | Size | SHA-256 |
|---|---|---|---|
| adapter_model.safetensors | Weights | 67.3 MB | 14ed7e1e9e85 |
| head.pt | Weights | 4.2 MB | ba758c41bfa5 |
| adapter_config.json | Configuration | 1.3 KB | — |
| training_config.json | Configuration | 1.6 KB | — |
| training_metrics.json | Configuration | 325 B | — |
| README.md | Documentation | 4.9 KB | — |
| chat_template.jinja | Other | 7.8 KB | — |
| .gitattributes | Repository | 1.6 KB | — |
| tokenizer.json | Tokenizer | 20.0 MB | 06b9509352d2 |
| tokenizer_config.json | Tokenizer | 1.1 KB | — |
License and Download
- License
- cc-by-nc-4.0
- Access
- Open weights, no gate
- Download size
- 71.5 MB
Download from Sae Chan O
Released by Sae Chan O through its official repository on Hugging Face. Read the license.
Built From
- Adapter of empero-ai/Qwen3.8-2B-Distill
- Derived from empero-ai/Qwen3.8-2B-Distill
Memory Requirements
| Precision | Weights in memory |
|---|---|
| As published | 71.5 MB |
Weights only, from the published parameter count; the key-value cache and runtime add to this.
Questions About malkuth-2b
Can I use malkuth-2b commercially?
Not without separate permission. malkuth-2b is released under Creative Commons Attribution-NonCommercial 4.0. CC BY-NC 4.0 permits sharing and adapting with credit for non-commercial purposes only. Commercial use needs separate permission from the rights holder.
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