qwen1.5-moe-chat#

  • Context Length: 32768

  • Model Name: qwen1.5-moe-chat

  • Languages: en, zh

  • Abilities: chat

  • 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: 4-bit, 8-bit, none

  • Engines: vLLM, Transformers (vLLM only available for quantization none)

  • 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

  • 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}