# Open-Weight Models Under cc-by-nc-nd-4.0: Open-Weight AI Source: https://savrn.com/models/licenses/cc-by-nc-nd-4-0 Markdown alternate of the page above; the site index is https://savrn.com/llms.txt --- SAVRN Model Hub · Models by License # Open-Weight Models Under cc-by-nc-nd-4.0 13 open-weight models released under cc-by-nc-nd-4.0 in the SAVRN Model Hub, with MaAI, Zikun Yang and Arif Akbarul Huda publishing the most. 13Models 9Publishers 86M to 278MParameter range 1Licenses ## Most Downloaded | Model | Publisher | Parameters | License | Monthly downloads | Cheapest GPUs at 16-bit | | --- | --- | --- | --- | --- | --- | | [nsfw-classifier](https://savrn.com/models/nsfw-classifier) | Giacomo Arienti | 86M | cc-by-nc-nd-4.0 | 259.1k | 1x MI300X, $1.85/hr | | [piiranha-v1-detect-personal-information](https://savrn.com/models/piiranha-v1-detect-personal-information) | The Internet Integrity Initiative | 278M | cc-by-nc-nd-4.0 | 245k | 1x MI300X, $1.85/hr | | [pertformer](https://savrn.com/models/pertformer) | Zikun Yang | — | cc-by-nc-nd-4.0 | 153 | — | | [CREformer](https://savrn.com/models/creformer) | Zikun Yang | — | cc-by-nc-nd-4.0 | 34 | — | | [CaputEmendatoris](https://savrn.com/models/caputemendatoris) | Aidan | — | cc-by-nc-nd-4.0 | 12 | — | | [vap_mc_ch](https://savrn.com/models/vap-mc-ch) | MaAI | — | cc-by-nc-nd-4.0 | — | — | | [vap_ch](https://savrn.com/models/vap-ch) | MaAI | — | cc-by-nc-nd-4.0 | — | — | | [vap_mc_en](https://savrn.com/models/vap-mc-en) | MaAI | — | cc-by-nc-nd-4.0 | — | — | | [vap_en](https://savrn.com/models/vap-en) | MaAI | — | cc-by-nc-nd-4.0 | — | — | | [JangMo](https://savrn.com/models/jangmo) | Kdh2342 | — | cc-by-nc-nd-4.0 | — | — | ## Who Publishes Them | Publisher | Models | | --- | --- | | [MaAI](https://savrn.com/model-publishers/maai-kyoto) | 4 | | [Zikun Yang](https://savrn.com/model-publishers/genomicintelligencedamoacademy) | 2 | | [Arif Akbarul Huda](https://savrn.com/model-publishers/omayib) | 1 | | [Korea Research Institute of Chemical Technology](https://savrn.com/model-publishers/krict-ai) | 1 | | [Kdh2342](https://savrn.com/model-publishers/kdh2342) | 1 | | [João13 \| Traduções & Dublagens](https://savrn.com/model-publishers/joao13traducoesdublagens) | 1 | ## All 13 Models Model · Image classification ### [nsfw-classifier](https://savrn.com/models/nsfw-classifier) [Giacomo Arienti](https://savrn.com/model-publishers/giacomoarienti) In today's digital world, user-generated content is a double-edged sword. While it fosters creativity and engagement, it also opens the door to inappropriate or illegal content being shared. Our NSFW Image Classifier is specifically designed to identify and filter out explicit images, including pornography, hentai, and sexually suggestive content, ensuring your platform remains safe, secure, and legally compliant. With more than 2M downloads, our NSFW Image Classifier has become the go-to solution for platforms looking to maintain a clean and safe environment for their users. Many developers and companies have already chosen our solution to protect their communities—will you be next? 1.… Open weights cc-by-nc-nd-4.0 86M parameters transformers [View model](https://savrn.com/models/nsfw-classifier) Model · Token classification ### [piiranha-v1-detect-personal-information](https://savrn.com/models/piiranha-v1-detect-personal-information) [The Internet Integrity Initiative](https://savrn.com/model-publishers/iiiorg) william (at) integrinet [dot] org Piiranha (cc-by-nc-nd-4.0 license) is trained to detect 17 types of Personally Identifiable Information (PII) across six languages. It successfully catches 98.27% of PII tokens, with an overall classification accuracy of 99.44%. Piiranha is especially accurate at detecting passwords, emails (100%), phone numbers, and usernames. Performance on PII vs. Non PII classification task: Piiranha was trained on H100 GPUs generously sponsored by the Akash Network Piiranha is a fine-tuned version of microsoft/mdeberta-v3-base. The context length is 256 Deberta tokens. If your text is longer than that, just split it up. Supported PII types: Account Number, Building… Open weights cc-by-nc-nd-4.0 278M parameters 512 tokens transformers [View model](https://savrn.com/models/piiranha-v1-detect-personal-information) Model ### [pertformer](https://savrn.com/models/pertformer) [Zikun Yang](https://savrn.com/model-publishers/genomicintelligencedamoacademy) This is the official pretrained model parameters of PertFormer: Zero-shot perturbation prediction and target discovery from wild-type biology Perturbation Transformer (PertFormer) is an LLM-based foundation model for zero-shot predictions of functional perturbations and cell fate dynamics. PertFormer has 3 billion parameters and was pretrained on massive bulk and single-cell multiomic data. Typically, without the need of task-specific training, PertFormer can realize the predictions of functional regulations, perturbations of genomic elements, genes, and sequences in a zero-shot manner, including the simulation of cell state transitions and disease treatment. This repository provides… Open weights cc-by-nc-nd-4.0 transformers [View model](https://savrn.com/models/pertformer) Model ### [CREformer](https://savrn.com/models/creformer) [Zikun Yang](https://savrn.com/model-publishers/genomicintelligencedamoacademy) This is the official pretrained model parameters of CREformer: Integrated bulk-single-cell foundation model enables zero-shot prediction of functional perturbations and cell fate dynamics. Cis-Regulatory Element Transformer (CREformer) is an LLM-based foundation model for zero-shot predictions of functional perturbations and cell fate dynamics. PertFormer has 3 billion parameters and was pretrained on massive bulk and single-cell multiomic data. Typically, without the need of task-specific training, PertFormer can realize the predictions of functional regulations, perturbations of genomic elements, genes, and sequences in a zero-shot manner, including the simulation of cell state… Open weights cc-by-nc-nd-4.0 [View model](https://savrn.com/models/creformer) Model · Token classification ### [CaputEmendatoris](https://savrn.com/models/caputemendatoris) [Aidan](https://savrn.com/model-publishers/aimgo) CaputEmendatoris is a projection head for Emendator trained to identify OCR artifacts in Latin text at a character level. You can use it to quantify the amount of damage to a sample or guide Emendator. The model is intended to be used on segments of 250 characters. Anything else will compromise performance. In initial testing, using 0.25 as a character probability threshold typically produced the best F1 score across all degrees of corruption. Orig: Cognoscenda virtute circumscripta est scientia, quae ad experientiam pertinet et ad rationem. OCR: C0gn0fccndauirtutccircurnfcriptacftfcientia:quacadcxpcricntiarnpcrtinct&adrationcrn« To use CaputEmendatoris, you can load it via the Transformers… Open weights cc-by-nc-nd-4.0 256 tokens [View model](https://savrn.com/models/caputemendatoris) Model · Tabular classification ### [badak](https://savrn.com/models/badak) [Arif Akbarul Huda](https://savrn.com/model-publishers/omayib) Open weights cc-by-nc-nd-4.0 scikit-learn [View model](https://savrn.com/models/badak) Model ### [JangMo](https://savrn.com/models/jangmo) [Kdh2342](https://savrn.com/model-publishers/kdh2342) Open weights cc-by-nc-nd-4.0 [View model](https://savrn.com/models/jangmo) Model ### [MARA](https://savrn.com/models/mara) [Korea Research Institute of Chemical Technology](https://savrn.com/model-publishers/krict-ai) Open weights cc-by-nc-nd-4.0 [View model](https://savrn.com/models/mara) Model ### [Traducoes](https://savrn.com/models/traducoes) [João13 | Traduções & Dublagens](https://savrn.com/model-publishers/joao13traducoesdublagens) Open weights cc-by-nc-nd-4.0 [View model](https://savrn.com/models/traducoes) Model ### [vap_ch](https://savrn.com/models/vap-ch) [MaAI](https://savrn.com/model-publishers/maai-kyoto) Open weights cc-by-nc-nd-4.0 [View model](https://savrn.com/models/vap-ch) Model ### [vap_en](https://savrn.com/models/vap-en) [MaAI](https://savrn.com/model-publishers/maai-kyoto) Open weights cc-by-nc-nd-4.0 [View model](https://savrn.com/models/vap-en) Model ### [vap_mc_ch](https://savrn.com/models/vap-mc-ch) [MaAI](https://savrn.com/model-publishers/maai-kyoto) Open weights cc-by-nc-nd-4.0 [View model](https://savrn.com/models/vap-mc-ch) Model ### [vap_mc_en](https://savrn.com/models/vap-mc-en) [MaAI](https://savrn.com/model-publishers/maai-kyoto) Open weights cc-by-nc-nd-4.0 [View model](https://savrn.com/models/vap-mc-en) ## Questions ### Which cc-by-nc-nd-4.0 models are most downloaded? By monthly downloads reported by the Hugging Face Hub: nsfw-classifier (259.1k); piiranha-v1-detect-personal-information (245k); pertformer (153). ## Other Licenses - [apache-2.0](https://savrn.com/models/licenses/apache-2-0) 3285 - [mit](https://savrn.com/models/licenses/mit) 1305 - [cc-by-nc-4.0](https://savrn.com/models/licenses/cc-by-nc-4-0) 209 - [cc-by-4.0](https://savrn.com/models/licenses/cc-by-4-0) 164 - [bsd-3-clause](https://savrn.com/models/licenses/bsd-3-clause) 108 - [gemma](https://savrn.com/models/licenses/gemma) 63 - [cc-by-nc-sa-4.0](https://savrn.com/models/licenses/cc-by-nc-sa-4-0) 52 - [llama3.2](https://savrn.com/models/licenses/llama3-2) 40 - [agpl-3.0](https://savrn.com/models/licenses/agpl-3-0) 32 - [unknown](https://savrn.com/models/licenses/unknown) 32 - [llama3.1](https://savrn.com/models/licenses/llama3-1) 28 - [cc-by-sa-4.0](https://savrn.com/models/licenses/cc-by-sa-4-0) 20 [See all](https://savrn.com/models/licenses)