llama-3.1-instruct#

  • Context Length: 131072

  • Model Name: llama-3.1-instruct

  • Languages: en, de, fr, it, pt, hi, es, th

  • Abilities: chat, tools

  • Description: The Llama 3.1 instruction tuned models are optimized for dialogue use cases and outperform many of the available open source chat models on common industry benchmarks..

Specifications#

Model Spec 1 (ggufv2, 8 Billion)#

  • Model Format: ggufv2

  • Model Size (in billions): 8

  • Quantizations: Q3_K_L, IQ4_XS, Q4_K_M, Q5_K_M, Q6_K, Q8_0

  • Engines: llama.cpp

  • Model ID: lmstudio-community/Meta-Llama-3.1-8B-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 llama-3.1-instruct --size-in-billions 8 --model-format ggufv2 --quantization ${quantization}

Model Spec 2 (pytorch, 8 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 8

  • Quantizations: none

  • Engines: vLLM, Transformers, SGLang

  • Model ID: meta-llama/Meta-Llama-3.1-8B-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 llama-3.1-instruct --size-in-billions 8 --model-format pytorch --quantization ${quantization}

Model Spec 3 (pytorch, 8 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 8

  • Quantizations: 4-bit

  • Engines: Transformers

  • Model ID: unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit

  • 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 llama-3.1-instruct --size-in-billions 8 --model-format pytorch --quantization ${quantization}

Model Spec 4 (gptq, 8 Billion)#

  • Model Format: gptq

  • Model Size (in billions): 8

  • Quantizations: Int4

  • Engines: vLLM, Transformers, SGLang

  • Model ID: hugging-quants/Meta-Llama-3.1-8B-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 llama-3.1-instruct --size-in-billions 8 --model-format gptq --quantization ${quantization}

Model Spec 5 (awq, 8 Billion)#

  • Model Format: awq

  • Model Size (in billions): 8

  • Quantizations: Int4

  • Engines: vLLM, Transformers, SGLang

  • Model ID: hugging-quants/Meta-Llama-3.1-8B-Instruct-AWQ-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 llama-3.1-instruct --size-in-billions 8 --model-format awq --quantization ${quantization}

Model Spec 6 (ggufv2, 70 Billion)#

  • Model Format: ggufv2

  • Model Size (in billions): 70

  • Quantizations: IQ2_M, IQ4_XS, Q2_K, Q3_K_S, Q4_K_M, Q5_K_M, Q6_K, Q8_0

  • Engines: llama.cpp

  • Model ID: lmstudio-community/Meta-Llama-3.1-70B-Instruct-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 llama-3.1-instruct --size-in-billions 70 --model-format ggufv2 --quantization ${quantization}

Model Spec 7 (pytorch, 70 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 70

  • Quantizations: none

  • Engines: vLLM, Transformers, SGLang

  • Model ID: meta-llama/Meta-Llama-3.1-70B-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 llama-3.1-instruct --size-in-billions 70 --model-format pytorch --quantization ${quantization}

Model Spec 8 (pytorch, 70 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 70

  • Quantizations: 4-bit

  • Engines: Transformers

  • Model ID: unsloth/Meta-Llama-3.1-70B-Instruct-bnb-4bit

  • 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 llama-3.1-instruct --size-in-billions 70 --model-format pytorch --quantization ${quantization}

Model Spec 9 (gptq, 70 Billion)#

  • Model Format: gptq

  • Model Size (in billions): 70

  • Quantizations: Int4

  • Engines: vLLM, Transformers, SGLang

  • Model ID: hugging-quants/Meta-Llama-3.1-70B-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 llama-3.1-instruct --size-in-billions 70 --model-format gptq --quantization ${quantization}

Model Spec 10 (awq, 70 Billion)#

  • Model Format: awq

  • Model Size (in billions): 70

  • Quantizations: Int4

  • Engines: vLLM, Transformers, SGLang

  • Model ID: hugging-quants/Meta-Llama-3.1-70B-Instruct-AWQ-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 llama-3.1-instruct --size-in-billions 70 --model-format awq --quantization ${quantization}

Model Spec 11 (mlx, 8 Billion)#

  • Model Format: mlx

  • Model Size (in billions): 8

  • Quantizations: 4-bit

  • Engines: MLX

  • Model ID: mlx-community/Meta-Llama-3.1-8B-Instruct-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 llama-3.1-instruct --size-in-billions 8 --model-format mlx --quantization ${quantization}

Model Spec 12 (mlx, 8 Billion)#

  • Model Format: mlx

  • Model Size (in billions): 8

  • Quantizations: 8-bit

  • Engines: MLX

  • Model ID: mlx-community/Meta-Llama-3.1-8B-Instruct-8bit

  • 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 llama-3.1-instruct --size-in-billions 8 --model-format mlx --quantization ${quantization}

Model Spec 13 (mlx, 8 Billion)#

  • Model Format: mlx

  • Model Size (in billions): 8

  • Quantizations: none

  • Engines: MLX

  • Model ID: mlx-community/Meta-Llama-3.1-8B-Instruct

  • 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 llama-3.1-instruct --size-in-billions 8 --model-format mlx --quantization ${quantization}

Model Spec 14 (mlx, 70 Billion)#

  • Model Format: mlx

  • Model Size (in billions): 70

  • Quantizations: 4-bit

  • Engines: MLX

  • Model ID: mlx-community/Meta-Llama-3.1-70B-Instruct-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 llama-3.1-instruct --size-in-billions 70 --model-format mlx --quantization ${quantization}

Model Spec 15 (mlx, 70 Billion)#

  • Model Format: mlx

  • Model Size (in billions): 70

  • Quantizations: 8-bit

  • Engines: MLX

  • Model ID: mlx-community/Meta-Llama-3.1-70B-Instruct-8bit

  • 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 llama-3.1-instruct --size-in-billions 70 --model-format mlx --quantization ${quantization}

Model Spec 16 (mlx, 70 Billion)#

  • Model Format: mlx

  • Model Size (in billions): 70

  • Quantizations: none

  • Engines: MLX

  • Model ID: mlx-community/Meta-Llama-3.1-70B-Instruct-bf16

  • 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 llama-3.1-instruct --size-in-billions 70 --model-format mlx --quantization ${quantization}

Model Spec 17 (pytorch, 405 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 405

  • Quantizations: 4-bit, 8-bit, none

  • Engines: vLLM, Transformers, SGLang (vLLM and SGLang only available for quantization none)

  • Model ID: meta-llama/Meta-Llama-3.1-405B-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 llama-3.1-instruct --size-in-billions 405 --model-format pytorch --quantization ${quantization}

Model Spec 18 (gptq, 405 Billion)#

  • Model Format: gptq

  • Model Size (in billions): 405

  • Quantizations: Int4

  • Engines: vLLM, Transformers, SGLang

  • Model ID: hugging-quants/Meta-Llama-3.1-405B-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 llama-3.1-instruct --size-in-billions 405 --model-format gptq --quantization ${quantization}

Model Spec 19 (awq, 405 Billion)#

  • Model Format: awq

  • Model Size (in billions): 405

  • Quantizations: Int4

  • Engines: vLLM, Transformers, SGLang

  • Model ID: hugging-quants/Meta-Llama-3.1-405B-Instruct-AWQ-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 llama-3.1-instruct --size-in-billions 405 --model-format awq --quantization ${quantization}