Text Generation
MLX
Safetensors
Korean
English
gemma3_text
gemma3
intent-classification
talkplay
conversational
8-bit precision
Instructions to use jaewon2/talkplay-intent-router-8bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use jaewon2/talkplay-intent-router-8bit with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("jaewon2/talkplay-intent-router-8bit") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- MLX LM
How to use jaewon2/talkplay-intent-router-8bit with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "jaewon2/talkplay-intent-router-8bit"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "jaewon2/talkplay-intent-router-8bit" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jaewon2/talkplay-intent-router-8bit", "messages": [ {"role": "user", "content": "Hello"} ] }'
TalkPlay Intent Router (Gemma 3 1B, fused LoRA, 8-bit)
On-device intent router for the TalkPlay hands-free YouTube voice player. Maps a spoken Korean/English utterance directly to a single TalkPlay intent JSON — no system prompt required; the tool definitions live in the fine-tuned weights.
- Base: Gemma 3 1B instruct (bf16), LoRA fine-tuned on 1,638 synthesized utterances covering all 78 TalkPlay intents (ko/en, STT-style variants), then fused and post-training quantized to 8-bit (group size 64).
- Eval: 54/54 (100%) on the shared TalkPlay router suite; ~0.4 s per command on M-series hardware (vs ~6.8 s for the previous Gemma 3 4B + 1,400-token-prompt setup).
- Usage: send the raw utterance as the user message with the bundled chat
template. Output is one JSON object, e.g.
{"intent": "SEARCH", "query": "calm jazz"}.
Training pipeline: Tools/agent-router in the TalkPlay repository.
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Model size
0.4B params
Tensor type
BF16
·
U32 ·
Hardware compatibility
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8-bit
Model tree for jaewon2/talkplay-intent-router-8bit
Base model
google/gemma-3-1b-pt Finetuned
google/gemma-3-1b-it Finetuned
mlx-community/gemma-3-1b-it-bf16