Text Generation
LiteRT-LM
English
agriculture
farmer-advisory
on-device
edge-ai
LiteRT-LM
LiteRT
qwen
LoRA
Indian-agriculture
Instructions to use uralstech/Qwen-2.5-1.5B-KCC-LiteRT-LM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT-LM
How to use uralstech/Qwen-2.5-1.5B-KCC-LiteRT-LM with LiteRT-LM:
# LiteRT-LM runs on various platforms (Android, iOS, Windows, Linux, macOS, IoT, Web/WASM) # and supports many APIs (C++, Python, Kotlin, Swift, JavaScript, Flutter). # For platform-specific integration guides, please refer to the official developer website: # https://ai.google.dev/edge/litert-lm # To try LiteRT-LM, the easiest way is to use our CLI tool. # 1. Install the LiteRT-LM CLI tool: pip install -U litert-lm # 2. Download and run this model locally: # See: https://ai.google.dev/edge/litert-lm/cli litert-lm run \ --from-huggingface-repo=uralstech/Qwen-2.5-1.5B-KCC-LiteRT-LM \ --prompt="Write me a poem"
- Notebooks
- Google Colab
- Kaggle
| Qwen-2.5-1.5B-KCC-LiteRT-LM | |
| Copyright 2025 URAV ADVANCED LEARNING SYSTEMS PRIVATE LIMITED | |
| This model was built using the pipeline described in the following project: | |
| https://uralstech.github.io/Qwen-KCC-On-Device-Pipeline |