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llama-2#

  • Context Length: 4096

  • Model Name: llama-2

  • Languages: en

  • Abilities: generate

  • Description: Llama-2 is the second generation of Llama, open-source and trained on a larger amount of data.

Specifications#

Model Spec 1 (ggmlv3, 7 Billion)#

  • Model Format: ggmlv3

  • Model Size (in billions): 7

  • 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: TheBloke/Llama-2-7B-GGML

  • 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-2 --size-in-billions 7 --model-format ggmlv3 --quantization ${quantization}

Model Spec 2 (gptq, 7 Billion)#

  • Model Format: gptq

  • Model Size (in billions): 7

  • Quantizations: Int4

  • Model ID: TheBloke/Llama-2-7B-GPTQ

  • 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-2 --size-in-billions 7 --model-format gptq --quantization ${quantization}

Model Spec 3 (awq, 7 Billion)#

  • Model Format: awq

  • Model Size (in billions): 7

  • Quantizations: Int4

  • Model ID: TheBloke/Llama-2-7B-AWQ

  • 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-2 --size-in-billions 7 --model-format awq --quantization ${quantization}

Model Spec 4 (ggmlv3, 13 Billion)#

  • Model Format: ggmlv3

  • Model Size (in billions): 13

  • 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: TheBloke/Llama-2-13B-GGML

  • 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-2 --size-in-billions 13 --model-format ggmlv3 --quantization ${quantization}

Model Spec 5 (ggmlv3, 70 Billion)#

  • Model Format: ggmlv3

  • Model Size (in billions): 70

  • 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: TheBloke/Llama-2-70B-GGML

  • 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-2 --size-in-billions 70 --model-format ggmlv3 --quantization ${quantization}

Model Spec 6 (pytorch, 7 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 7

  • Quantizations: 4-bit, 8-bit, none

  • Model ID: meta-llama/Llama-2-7b-hf

  • 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-2 --size-in-billions 7 --model-format pytorch --quantization ${quantization}

Model Spec 7 (pytorch, 13 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 13

  • Quantizations: 4-bit, 8-bit, none

  • Model ID: meta-llama/Llama-2-13b-hf

  • 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-2 --size-in-billions 13 --model-format pytorch --quantization ${quantization}

Model Spec 8 (gptq, 13 Billion)#

  • Model Format: gptq

  • Model Size (in billions): 13

  • Quantizations: Int4

  • Model ID: TheBloke/Llama-2-13B-GPTQ

  • 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-2 --size-in-billions 13 --model-format gptq --quantization ${quantization}

Model Spec 9 (awq, 13 Billion)#

  • Model Format: awq

  • Model Size (in billions): 13

  • Quantizations: Int4

  • Model ID: TheBloke/Llama-2-13B-AWQ

  • 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-2 --size-in-billions 13 --model-format awq --quantization ${quantization}

Model Spec 10 (pytorch, 70 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 70

  • Quantizations: 4-bit, 8-bit, none

  • Model ID: meta-llama/Llama-2-70b-hf

  • 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-2 --size-in-billions 70 --model-format pytorch --quantization ${quantization}

Model Spec 11 (gptq, 70 Billion)#

  • Model Format: gptq

  • Model Size (in billions): 70

  • Quantizations: Int4

  • Model ID: TheBloke/Llama-2-70B-GPTQ

  • 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-2 --size-in-billions 70 --model-format gptq --quantization ${quantization}

Model Spec 12 (awq, 70 Billion)#

  • Model Format: awq

  • Model Size (in billions): 70

  • Quantizations: Int4

  • Model ID: TheBloke/Llama-2-70B-AWQ

  • 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-2 --size-in-billions 70 --model-format awq --quantization ${quantization}
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