llama-3

• Context Length: 8192

• Model Name: llama-3

• Languages: en

• Abilities: generate

• Description: Llama 3 is an auto-regressive language model that uses an optimized transformer architecture

Specifications

Model Spec 1 (pytorch, 8 Billion)

• Model Format: pytorch

• Model Size (in billions): 8

• Quantizations: 4-bit, 8-bit, none

• Model ID: meta-llama/Meta-Llama-3-8B

• 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-name llama-3 --size-in-billions 8 --model-format pytorch --quantization ${quantization}

Model Spec 2 (ggufv2, 8 Billion)

• Model Format: ggufv2

• Model Size (in billions): 8

• Quantizations: Q2_K, Q3_K_L, Q3_K_M, Q3_K_S, Q4_0, Q4_1, Q4_K_M, Q4_K_S, Q5_0, Q5_1, Q5_K_M, Q5_K_S, Q6_K, Q8_0

• Model ID: QuantFactory/Meta-Llama-3-8B-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-name llama-3 --size-in-billions 8 --model-format ggufv2 --quantization ${quantization}

Model Spec 3 (pytorch, 70 Billion)

• Model Format: pytorch

• Model Size (in billions): 70

• Quantizations: 4-bit, 8-bit, none

• Model ID: meta-llama/Meta-Llama-3-70B

• 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-name llama-3 --size-in-billions 70 --model-format pytorch --quantization ${quantization}

Model Spec 4 (ggufv2, 70 Billion)

• Model Format: ggufv2

• Model Size (in billions): 70

• Quantizations: Q4_K_M, Q5_K_M

• Model ID: NousResearch/Meta-Llama-3-70B-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-name llama-3 --size-in-billions 70 --model-format ggufv2 --quantization ${quantization}