internlm3-instruct#
Context Length: 32768
Model Name: internlm3-instruct
Languages: en, zh
Abilities: chat, tools
Description: InternLM3 has open-sourced an 8-billion parameter instruction model, InternLM3-8B-Instruct, designed for general-purpose usage and advanced reasoning.
Specifications#
Model Spec 1 (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: internlm/internlm3-8b-instruct
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 internlm3-instruct --size-in-billions 8 --model-format pytorch --quantization ${quantization}
Model Spec 2 (gptq, 8 Billion)#
Model Format: gptq
Model Size (in billions): 8
Quantizations: Int4
Engines: vLLM, Transformers
Model ID: internlm/internlm3-8b-instruct-gptq-int4
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 internlm3-instruct --size-in-billions 8 --model-format gptq --quantization ${quantization}
Model Spec 3 (awq, 8 Billion)#
Model Format: awq
Model Size (in billions): 8
Quantizations: Int4
Engines: vLLM, Transformers
Model ID: internlm/internlm3-8b-instruct-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 internlm3-instruct --size-in-billions 8 --model-format awq --quantization ${quantization}
Model Spec 4 (ggufv2, 8 Billion)#
Model Format: ggufv2
Model Size (in billions): 8
Quantizations: q2_k, q3_k_m, q4_0, q4_k_m, q5_0, q5_k_m, q6_k, q8_0
Engines: llama.cpp
Model ID: internlm/internlm3-8b-instruct-gguf
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 internlm3-instruct --size-in-billions 8 --model-format ggufv2 --quantization ${quantization}
Model Spec 5 (mlx, 8 Billion)#
Model Format: mlx
Model Size (in billions): 8
Quantizations: 4bit
Engines: MLX
Model ID: mlx-community/internlm3-8b-instruct-{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 internlm3-instruct --size-in-billions 8 --model-format mlx --quantization ${quantization}