orca

• Context Length: 2048

• Model Name: orca

• Languages: en

• Abilities: chat

• Description: Orca is an LLM trained by fine-tuning LLaMA on explanation traces obtained from GPT-4.

Specifications

Model Spec 1 (ggmlv3, 3 Billion)

• Model Format: ggmlv3

• Model Size (in billions): 3

• Quantizations: q4_0, q4_1, q5_0, q5_1, q8_0

• Model ID: TheBloke/orca_mini_3B-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 orca --size-in-billions 3 --model-format ggmlv3 --quantization ${quantization}

Model Spec 2 (ggmlv3, 7 Billion)

• Model Format: ggmlv3

• Model Size (in billions): 7

• Quantizations: q4_0, q4_1, q5_0, q5_1, q8_0

• Model ID: TheBloke/orca_mini_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 orca --size-in-billions 7 --model-format ggmlv3 --quantization ${quantization}

Model Spec 3 (ggmlv3, 13 Billion)

• Model Format: ggmlv3

• Model Size (in billions): 13

• Quantizations: q4_0, q4_1, q5_0, q5_1, q8_0

• Model ID: TheBloke/orca_mini_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 orca --size-in-billions 13 --model-format ggmlv3 --quantization ${quantization}