deberta-v3-base-prompt-injection-v2
> [!WARNING] > THIS PROJECT HAS BEEN ARCHIVED. > > This project and its associated code on GitHub are no longer under active development or maintained.
Params
180 M
Context
512
Downloads 30d
859 K
Likes
117
Download history
daily snapshots · 55 days
▲ 377 K in the last 30 days (78.0%)
870 K500 K
Aug 22Sep 1Sep 11Sep 20
870 K272 K
Jul 28Aug 15Sep 2Sep 20
Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| model.safetensors | f32 | 0.7 GB | 1.3 GB | ✅ Runs comfortably |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Specifications
- Architecture
- DebertaV2ForSequenceClassification
- Parameters
- 180 M
- Tensor type
- F32
- Context length
- 512
- Vocabulary
- 128,100
- Layers / heads
- 12 / 12
- Licence
- apache-2.0
- First seen on the Hub
- 2024-04-20
- Training datasets
- natolambert/xstest-v2-copy, VMware/open-instruct, alespalla/chatbot_instruction_prompts, HuggingFaceH4/grok-conversation-harmless, Harelix/Prompt-Injection-Mixed-Techniques-2024, OpenSafetyLab/Salad-Data, jackhhao/jailbreak-classification
- Added to our catalog
- 2026-07-28
Compare with any text-classification model