.. _models_llm_internvl2.5: ======================================== InternVL2.5 ======================================== - **Context Length:** 16384 - **Model Name:** InternVL2.5 - **Languages:** en, zh - **Abilities:** chat, vision - **Description:** InternVL 2.5 is an open-source multimodal large language model (MLLM) to bridge the capability gap between open-source and proprietary commercial models in multimodal understanding. Specifications ^^^^^^^^^^^^^^ Model Spec 1 (pytorch, 1 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** pytorch - **Model Size (in billions):** 1 - **Quantizations:** 4-bit, 8-bit, none - **Engines**: vLLM, Transformers (vLLM only available for quantization none) - **Model ID:** OpenGVLab/InternVL2_5-1B - **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 InternVL2.5 --size-in-billions 1 --model-format pytorch --quantization ${quantization} Model Spec 2 (pytorch, 2 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** pytorch - **Model Size (in billions):** 2 - **Quantizations:** 4-bit, 8-bit, none - **Engines**: vLLM, Transformers (vLLM only available for quantization none) - **Model ID:** OpenGVLab/InternVL2_5-2B - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name InternVL2.5 --size-in-billions 2 --model-format pytorch --quantization ${quantization} Model Spec 3 (pytorch, 4 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** pytorch - **Model Size (in billions):** 4 - **Quantizations:** 4-bit, 8-bit, none - **Engines**: vLLM, Transformers (vLLM only available for quantization none) - **Model ID:** OpenGVLab/InternVL2_5-4B - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name InternVL2.5 --size-in-billions 4 --model-format pytorch --quantization ${quantization} Model Spec 4 (awq, 4 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** awq - **Model Size (in billions):** 4 - **Quantizations:** Int4 - **Engines**: vLLM, Transformers - **Model ID:** OpenGVLab/InternVL2_5-4B-AWQ - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name InternVL2.5 --size-in-billions 4 --model-format awq --quantization ${quantization} Model Spec 5 (pytorch, 8 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** pytorch - **Model Size (in billions):** 8 - **Quantizations:** 4-bit, 8-bit, none - **Engines**: vLLM, Transformers (vLLM only available for quantization none) - **Model ID:** OpenGVLab/InternVL2_5-8B - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name InternVL2.5 --size-in-billions 8 --model-format pytorch --quantization ${quantization} Model Spec 6 (awq, 8 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** awq - **Model Size (in billions):** 8 - **Quantizations:** Int4 - **Engines**: vLLM, Transformers - **Model ID:** OpenGVLab/InternVL2_5-8B-AWQ - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name InternVL2.5 --size-in-billions 8 --model-format awq --quantization ${quantization} Model Spec 7 (pytorch, 26 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** pytorch - **Model Size (in billions):** 26 - **Quantizations:** 4-bit, 8-bit, none - **Engines**: vLLM, Transformers (vLLM only available for quantization none) - **Model ID:** OpenGVLab/InternVL2_5-26B - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name InternVL2.5 --size-in-billions 26 --model-format pytorch --quantization ${quantization} Model Spec 8 (awq, 26 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** awq - **Model Size (in billions):** 26 - **Quantizations:** Int4 - **Engines**: vLLM, Transformers - **Model ID:** OpenGVLab/InternVL2_5-26B-AWQ - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name InternVL2.5 --size-in-billions 26 --model-format awq --quantization ${quantization} Model Spec 9 (pytorch, 38 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** pytorch - **Model Size (in billions):** 38 - **Quantizations:** 4-bit, 8-bit, none - **Engines**: vLLM, Transformers (vLLM only available for quantization none) - **Model ID:** OpenGVLab/InternVL2_5-38B - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name InternVL2.5 --size-in-billions 38 --model-format pytorch --quantization ${quantization} Model Spec 10 (awq, 38 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** awq - **Model Size (in billions):** 38 - **Quantizations:** Int4 - **Engines**: vLLM, Transformers - **Model ID:** OpenGVLab/InternVL2_5-38B-AWQ - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name InternVL2.5 --size-in-billions 38 --model-format awq --quantization ${quantization} Model Spec 11 (pytorch, 78 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** pytorch - **Model Size (in billions):** 78 - **Quantizations:** 4-bit, 8-bit, none - **Engines**: vLLM, Transformers (vLLM only available for quantization none) - **Model ID:** OpenGVLab/InternVL2_5-78B - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name InternVL2.5 --size-in-billions 78 --model-format pytorch --quantization ${quantization} Model Spec 12 (awq, 78 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** awq - **Model Size (in billions):** 78 - **Quantizations:** Int4 - **Engines**: vLLM, Transformers - **Model ID:** OpenGVLab/InternVL2_5-78B-AWQ - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name InternVL2.5 --size-in-billions 78 --model-format awq --quantization ${quantization}