Gemma 3 12B multimodal base
According to the model card, the model is a fine-tuned multimodal model on Gemma 3 12B Instruct with a SigLIP vision encoder.
Open Source Model Profile · Ryex
Floppa-12B-Gemma3-Uncensored is a 12.19B-parameter Gemma 3 multimodal fine-tune from Ryex for uncensored Japanese-English translation and image description.
Floppa-12B-Gemma3-Uncensored is published by Ryex as a Gemma3 image-text-to-text fine-tune. The captured configuration identifies Gemma3ForConditionalGeneration and Safetensors metadata reports 12,187,325,040 parameters. According to the model card, it is based on Gemma 3 12B Instruct for uncensored translation and image description, and card data records gemma.
According to the model card, the model is a fine-tuned multimodal model on Gemma 3 12B Instruct with a SigLIP vision encoder.
The publisher says it performs Japanese-English translation and image description with zero sanitization, including slang, profanity, and cultural nuance.
According to the model card, 4-bit QLoRA with Unsloth was merged to bfloat16 after training on about 10.5k rows with toxic-text and vision-anchor mixes.
According to the model card, the model is optimized for vLLM with a documented image-plus-prompt generation example.
Source: Ryex/Floppa-12B-Gemma3-Uncensored
Captured: Unknown. Processed: 2026-09-07T19:35:51.536096+00:00.
Floppa-12B-Gemma3 (Uncensored) Floppa-12B is a fine-tuned multimodal model based on Google's Gemma 3 12B Instruct . It has been specialized for high-fidelity uncensored translation (Japanese <-> English) and unrestricted image description . Unlike the base model, Floppa does not refuse to describe explicit, violent, or "spicy" imagery, and it translates slang, profanity, and cultural nuances with zero sanitization. Model Description Base Model: google/gemma-3-12b-it Architecture: 12B Dense Transformer with SigLIP Vision Encoder (Hybrid Attention). Training Method: 4-bit QLoRA with Unsloth, merged to bfloat16. Objective: Behavior mod…
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