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# JoyAI-VL-Interaction-Preview-AWQ
AWQ W4A16 post-training quantization (PTQ) of [`jdopensource/JoyAI-VL-Interaction-Preview`](https://huggingface.co/jdopensource/JoyAI-VL-Interaction-Preview).
This model card focuses on **how the quantized checkpoint was produced**, not on how to consume the model (for inference usage please refer to the base model card).
## Base Model
| Attribute | Value |
|---|---|
| **Base model** | `jdopensource/JoyAI-VL-Interaction-Preview` |
| **Architecture** | `Qwen3VLForConditionalGeneration` |
| **Scale** | ~8B parameters |
| **Original dtype** | `bfloat16` |
## Quantization Method
| Attribute | Value |
|---|---|
| **Method** | AWQ — Activation-aware Weight Quantization |
| **Tool** | [`llmcompressor`](https://github.com/vllm-project/llm-compressor) |
| **API used** | `llmcompressor.oneshot()` with `AWQModifier` |
| **Quantization scheme** | W4A16 (4-bit weights, 16-bit activations) |
| **Format** | `compressed-tensors` (`quant_method: "compressed-tens… -
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