qwen2.5#
Context Length: 32768
Model Name: qwen2.5
Languages: en, zh
Abilities: generate
Description: Qwen2.5 is the latest series of Qwen large language models. For Qwen2.5, we release a number of base language models and instruction-tuned language models ranging from 0.5 to 72 billion parameters.
Specifications#
Model Spec 1 (pytorch, 0_5 Billion)#
Model Format: pytorch
Model Size (in billions): 0_5
Quantizations: 4-bit, 8-bit, none
Engines: vLLM, Transformers, SGLang (vLLM and SGLang only available for quantization none)
Model ID: Qwen/Qwen2.5-0.5B
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 qwen2.5 --size-in-billions 0_5 --model-format pytorch --quantization ${quantization}
Model Spec 2 (pytorch, 1_5 Billion)#
Model Format: pytorch
Model Size (in billions): 1_5
Quantizations: 4-bit, 8-bit, none
Engines: vLLM, Transformers, SGLang (vLLM and SGLang only available for quantization none)
Model ID: Qwen/Qwen2.5-1.5B
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 qwen2.5 --size-in-billions 1_5 --model-format pytorch --quantization ${quantization}
Model Spec 3 (pytorch, 3 Billion)#
Model Format: pytorch
Model Size (in billions): 3
Quantizations: 4-bit, 8-bit, none
Engines: vLLM, Transformers, SGLang (vLLM and SGLang only available for quantization none)
Model ID: Qwen/Qwen2.5-3B
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 qwen2.5 --size-in-billions 3 --model-format pytorch --quantization ${quantization}
Model Spec 4 (pytorch, 7 Billion)#
Model Format: pytorch
Model Size (in billions): 7
Quantizations: 4-bit, 8-bit, none
Engines: vLLM, Transformers, SGLang (vLLM and SGLang only available for quantization none)
Model ID: Qwen/Qwen2.5-7B
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 qwen2.5 --size-in-billions 7 --model-format pytorch --quantization ${quantization}
Model Spec 5 (pytorch, 14 Billion)#
Model Format: pytorch
Model Size (in billions): 14
Quantizations: 4-bit, 8-bit, none
Engines: vLLM, Transformers, SGLang (vLLM and SGLang only available for quantization none)
Model ID: Qwen/Qwen2.5-14B
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 qwen2.5 --size-in-billions 14 --model-format pytorch --quantization ${quantization}
Model Spec 6 (pytorch, 32 Billion)#
Model Format: pytorch
Model Size (in billions): 32
Quantizations: 4-bit, 8-bit, none
Engines: vLLM, Transformers, SGLang (vLLM and SGLang only available for quantization none)
Model ID: Qwen/Qwen2.5-32B
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 qwen2.5 --size-in-billions 32 --model-format pytorch --quantization ${quantization}
Model Spec 7 (pytorch, 72 Billion)#
Model Format: pytorch
Model Size (in billions): 72
Quantizations: 4-bit, 8-bit, none
Engines: vLLM, Transformers, SGLang (vLLM and SGLang only available for quantization none)
Model ID: Qwen/Qwen2.5-72B
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 qwen2.5 --size-in-billions 72 --model-format pytorch --quantization ${quantization}