| --- |
| language: en |
| library_name: litert-lm |
| tags: |
| - on-device |
| - gemma |
| - gemma-4 |
| - ai-text-detection |
| - bouncer |
| --- |
| |
| # Gemma 4 E4B IT — Bouncer on-device classifier |
|
|
| `.litertlm` bundle and hot-swappable LoRA adapter for the |
| [imbue-ai/bouncer-private](https://github.com/imbue-ai/bouncer-private) |
| iOS app, intended to be consumed by a forked LiteRT-LM runtime |
| (millanatimbue/LiteRT-LM @ expose-aux-tensor-outputs). |
|
|
| ## Contents |
|
|
| | File | Size | Purpose | |
| |---|---|---| |
| | `model.litertlm` | 3.9 GB | Gemma 4 E4B IT base + classifier head + LoRA tensor input slots | |
| | `lora_adapter.tflite` | 18 MB | Attention-only LoRA (rank=8) hot-swapped at session creation | |
| | `tokenizer.json`, `tokenizer_config.json` | reference copies (also embedded in `model.litertlm`) | |
|
|
| ## How it's used |
|
|
| ```swift |
| let conv = try await engine.createConversation(with: cfg) |
| try conv.setScopedLoraFile(loraAdapterURL) // hot-swap LoRA |
| try await conv.sendMessage(.text(text), // prefill + 1 decode step |
| optionalArgs: .init(maxOutputTokens: 1)) |
| let logits = try conv.getAuxiliaryOutput(name: "classifier_logits") |
| // argmax(logits) → bucket 0 (human) ... bucket 3 (AI) |
| ``` |
|
|
| For generation (no classification), don't call `setScopedLoraFile` — |
| LoRA inputs default to zero and the model runs as base IT. |
|
|
| ## Build details |
|
|
| - Quantization: `gemma4_mixed48` (Google's recommended Gemma 4 mixed |
| int4/int8 recipe; same family as upstream |
| `litert-community/gemma-4-E4B-it-litert-lm`) |
| - Cache length: 1024 tokens (matches iOS `EngineConfig.maxNumTokens`) |
| - Source: `google/gemma-4-E4B-it` text decoder, fine-tuned with PEFT |
| attention-only LoRA + a 4-class NormedLinear head (LayerNorm + |
| Linear) over the last input token's hidden state. |
| - Conversion: forked `google-ai-edge/litert-torch` with Gemma 4 |
| classifier_head + LoRA-input wiring (see |
| [EditLens](https://github.com/pangramlabs/EditLens) for the |
| converter patches). |
| |
