.. _models_llm_xverse: ======================================== xverse ======================================== - **Context Length:** 2048 - **Model Name:** xverse - **Languages:** en, zh - **Abilities:** generate - **Description:** XVERSE is a multilingual large language model, independently developed by Shenzhen Yuanxiang Technology. Specifications ^^^^^^^^^^^^^^ Model Spec 1 (pytorch, 7 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** pytorch - **Model Size (in billions):** 7 - **Quantizations:** none - **Engines**: Transformers - **Model ID:** xverse/XVERSE-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 xverse --size-in-billions 7 --model-format pytorch --quantization ${quantization} Model Spec 2 (pytorch, 13 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** pytorch - **Model Size (in billions):** 13 - **Quantizations:** none - **Engines**: Transformers - **Model ID:** xverse/XVERSE-13B - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name xverse --size-in-billions 13 --model-format pytorch --quantization ${quantization} Model Spec 3 (pytorch, 65 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** pytorch - **Model Size (in billions):** 65 - **Quantizations:** none - **Engines**: Transformers - **Model ID:** xverse/XVERSE-65B - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name xverse --size-in-billions 65 --model-format pytorch --quantization ${quantization}