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vicuna-v1.3#

  • Context Length: 2048

  • Model Name: vicuna-v1.3

  • Languages: en

  • Abilities: chat

  • Description: Vicuna is an open-source LLM trained by fine-tuning LLaMA on data collected from ShareGPT.

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/vicuna-7B-v1.3-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 vicuna-v1.3 --size-in-billions 7 --model-format ggmlv3 --quantization ${quantization}

Model Spec 2 (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/vicuna-13b-v1.3.0-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 vicuna-v1.3 --size-in-billions 13 --model-format ggmlv3 --quantization ${quantization}

Model Spec 3 (ggmlv3, 33 Billion)#

  • Model Format: ggmlv3

  • Model Size (in billions): 33

  • 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/vicuna-33B-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 vicuna-v1.3 --size-in-billions 33 --model-format ggmlv3 --quantization ${quantization}

Model Spec 4 (pytorch, 33 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 33

  • Quantizations: 4-bit, 8-bit, none

  • Model ID: lmsys/vicuna-33b-v1.3

  • 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 vicuna-v1.3 --size-in-billions 33 --model-format pytorch --quantization ${quantization}

Model Spec 5 (pytorch, 13 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 13

  • Quantizations: 4-bit, 8-bit, none

  • Model ID: lmsys/vicuna-13b-v1.3

  • 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 vicuna-v1.3 --size-in-billions 13 --model-format pytorch --quantization ${quantization}

Model Spec 6 (pytorch, 7 Billion)#

  • Model Format: pytorch

  • Model Size (in billions): 7

  • Quantizations: 4-bit, 8-bit, none

  • Model ID: lmsys/vicuna-7b-v1.3

  • 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 vicuna-v1.3 --size-in-billions 7 --model-format pytorch --quantization ${quantization}
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