.. _models_llm_telechat: ======================================== telechat ======================================== - **Context Length:** 8192 - **Model Name:** telechat - **Languages:** en, zh - **Abilities:** chat - **Description:** The TeleChat is a large language model developed and trained by China Telecom Artificial Intelligence Technology Co., LTD. The 7B model base is trained with 1.5 trillion Tokens and 3 trillion Tokens and Chinese high-quality corpus. Specifications ^^^^^^^^^^^^^^ Model Spec 1 (pytorch, 7 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** pytorch - **Model Size (in billions):** 7 - **Quantizations:** 4-bit, 8-bit, none - **Engines**: Transformers - **Model ID:** Tele-AI/telechat-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 telechat --size-in-billions 7 --model-format pytorch --quantization ${quantization} Model Spec 2 (gptq, 7 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** gptq - **Model Size (in billions):** 7 - **Quantizations:** int4, int8 - **Engines**: Transformers - **Model ID:** Tele-AI/telechat-7B-{quantization} - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name telechat --size-in-billions 7 --model-format gptq --quantization ${quantization} Model Spec 3 (pytorch, 12 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** pytorch - **Model Size (in billions):** 12 - **Quantizations:** 4-bit, 8-bit, none - **Engines**: Transformers - **Model ID:** Tele-AI/TeleChat-12B - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name telechat --size-in-billions 12 --model-format pytorch --quantization ${quantization} Model Spec 4 (gptq, 12 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** gptq - **Model Size (in billions):** 12 - **Quantizations:** int4, int8 - **Engines**: Transformers - **Model ID:** Tele-AI/TeleChat-12B-{quantization} - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name telechat --size-in-billions 12 --model-format gptq --quantization ${quantization} Model Spec 5 (pytorch, 52 Billion) ++++++++++++++++++++++++++++++++++++++++ - **Model Format:** pytorch - **Model Size (in billions):** 52 - **Quantizations:** 4-bit, 8-bit, none - **Engines**: Transformers - **Model ID:** Tele-AI/TeleChat-52B - **Model Hubs**: `Hugging Face `__, `ModelScope `__ Execute the following command to launch the model, remember to replace ``${quantization}`` with your chosen quantization method from the options listed above:: xinference launch --model-engine ${engine} --model-name telechat --size-in-billions 52 --model-format pytorch --quantization ${quantization}