internlm2.5-chat-1m#

  • Context Length: 262144

  • Model Name: internlm2.5-chat-1m

  • Languages: en, zh

  • Abilities: chat

  • Description: InternLM2.5 series of the InternLM model supports 1M long-context

Specifications#

Model Spec 1 (pytorch, 7 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 7

  • Quantizations: none

  • Engines: vLLM, Transformers

  • Model ID: internlm/internlm2_5-7b-chat-1m

  • 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 internlm2.5-chat-1m --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

  • Engines: vLLM, Transformers

  • Model ID: ModelCloud/internlm-2.5-7b-chat-1m-gptq-4bit

  • Model Hubs: Hugging Face

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 internlm2.5-chat-1m --size-in-billions 7 --model-format gptq --quantization ${quantization}

Model Spec 3 (ggufv2, 7 Billion)#

  • Model Format: ggufv2

  • Model Size (in billions): 7

  • Quantizations: q2_k, q3_k_m, q4_0, q4_k_m, q5_0, q5_k_m, q6_k, q8_0, fp16

  • Engines: llama.cpp

  • Model ID: internlm/internlm2_5-7b-chat-1m-gguf

  • Model Hubs: Hugging Face

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 internlm2.5-chat-1m --size-in-billions 7 --model-format ggufv2 --quantization ${quantization}