Instructions to use litert-community/Qwen3-1.7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LiteRT-LM
How to use litert-community/Qwen3-1.7B 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 litert-lm # 2. Download and run this model locally: # See: https://ai.google.dev/edge/litert-lm/cli litert-lm run \ --from-huggingface-repo=litert-community/Qwen3-1.7B \ model.litertlm \ --prompt="Write me a poem"
- Notebooks
- Google Colab
- Kaggle
Qwen3-1.7B LiteRT-LM Model
This repository contains LiteRT-LM variants of Qwen/Qwen3-1.7B optimized for on-device text generation.
Available Artifact
| File | Quantization Recipe | Context | Size |
|---|---|---|---|
Qwen3_1.7B.litertlm |
dynamic_wi8_afp32 | - | 2.1 GB |
How to Use
Command-Line Interface
- Install the prerequisites:
pip install litert-lm
- Run the command in CLI:
litert-lm run --from-huggingface-repo=litert-community/Qwen3-1.7B Qwen3_1.7B.litertlm --prompt="Write me a poem on nature"
Python
- Install the prerequisites:
pip install litert-lm huggingface_hub
- Download the model file:
from huggingface_hub import hf_hub_download
model_path = hf_hub_download(
repo_id="litert-community/Qwen3-1.7B",
filename="Qwen3_1.7B.litertlm"
)
- Run inference:
import litert_lm
litert_lm.set_min_log_severity(litert_lm.LogSeverity.ERROR) # Hide log for TUI app
with litert_lm.Engine(model_path) as engine:
with engine.create_conversation() as conversation:
while True:
user_input = input("\n>>> ")
for chunk in conversation.send_message_async(user_input):
print(chunk["content"][0]["text"], end="", flush=True)
Integration
Ready to integrate this into your product? Get started in the LiteRT-LM documentation.
- Downloads last month
- 875