| --- |
| license: apache-2.0 |
| --- |
| # RWKV-7 60M Mobile Pretrained (English) |
|
|
| This is a pretrained language model based on the cutting-edge **RWKV-7** architecture, optimized specifically for local fine-tuning and inference directly on your **iPhone**. |
|
|
| Thanks to its ultra-lightweight design and the linear complexity of the RNN-like RWKV architecture, it delivers high performance, low latency, and minimal power consumption, making it an ideal choice for edge computing on mobile devices. |
|
|
| --- |
|
|
| ## 📊 Model Specifications |
|
|
| Below are the key technical parameters used by the application to initialize the network and tokenizer: |
|
|
| | Parameter | Value | |
| | :--- | :--- | |
| | **Architecture** | RWKV-7 | |
| | **Total Parameters** | 60M | |
| | **Layers** | 18 | |
| | **Hidden Size** | 448 | |
| | **Vocab Size** | 16,000 (16k) | |
| | **Tokenizer** | BPE (Byte-Pair Encoding) | |
| | **Primary Language** | English | |
| | **License** | Apache 2.0 | |
|
|
| --- |
|
|
| ## 📱 On-Device Fine-Tuning & Inference on iPhone |
|
|
| This model is tailored to fit within the strict RAM constraints of iOS. A footprint of ~60 million parameters allows you to perform local fine-tuning and text generation without overwhelming the device's available memory. |
|
|
| ### Key Mobile Features: |
| * **Low Memory Footprint:** Easily fits into RAM, leaving plenty of headroom for the application's UI and system processes. |
| * **Efficient BPE Tokenizer:** A 16k vocabulary optimized specifically for fast, low-overhead English text processing on mobile processors. |
| * **RWKV-7 Architecture Advantage:** Combines the generation quality of Transformers with the computational efficiency of RNNs, preserving your iPhone's battery life during inference and training. |
|
|
| > 💡 **Fine-Tuning Tip:** When training inside the app, we recommend using compact text datasets (such as personal notes, specific documentation, or custom dialogue logs). Local training ensures absolute privacy — your data never leaves your device. |
|
|
| --- |
|
|
| ## 🔒 License |
|
|
| This model and its weights are distributed under the **Apache 2.0** license. You are free to use, modify, and distribute it for both personal and commercial applications. |
|
|
| **ImpulseLeap / Alexei Goncharov** |
|
|
| www.impulseleap.com |
