.. _models_llm_qwen1.5-moe-chat: ======================================== qwen1.5-moe-chat ======================================== - **Context Length:** 32768 - **Model Name:** qwen1.5-moe-chat - **Languages:** en, zh - **Abilities:** chat, tools - **Description:** Qwen1.5-MoE is a transformer-based MoE decoder-only language model pretrained on a large amount of data. Specifications ^^^^^^^^^^^^^^ Model Spec 1 (pytorch, 2_7 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** pytorch - **Model Size (in billions):** 2_7 - **Quantizations:** none - **Engines**: vLLM, Transformers, SGLang - **Model ID:** Qwen/Qwen1.5-MoE-A2.7B-Chat - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name qwen1.5-moe-chat --size-in-billions 2_7 --model-format pytorch --quantization ${quantization} Model Spec 2 (gptq, 2_7 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** gptq - **Model Size (in billions):** 2_7 - **Quantizations:** Int4 - **Engines**: vLLM, Transformers, SGLang - **Model ID:** Qwen/Qwen1.5-MoE-A2.7B-Chat-GPTQ-Int4 - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name qwen1.5-moe-chat --size-in-billions 2_7 --model-format gptq --quantization ${quantization}