2 versions
A general-purpose model ranging from 3 billion parameters to 70 billion, suitable for entry-level hardware.
Install our magic
package manager:
curl -ssL https://magic.modular.com/ | bash
Then run the source
command that's printed in your terminal.
Install Max Pipelines in order to run this model.
magic global install max-pipelines
Start a local endpoint for orca-mini/3b:
max-serve serve --huggingface-repo-id pankajmathur/orca_mini_v9_7_3B-Instruct
The endpoint is ready when you see the URI printed in your terminal:
Uvicorn running on http://0.0.0.0:8000 (Press CTRL+C to quit)
Now open another terminal to send a request using curl
:
curl -N http://0.0.0.0:8000/v1/chat/completions -H "Content-Type: application/json" -d '{
"model": "orca-mini/3b",
"stream": true,
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Who won the World Series in 2020?"}
]
}' | grep -o '"content":"[^"]*"' | sed 's/"content":"//g' | sed 's/"//g' | tr -d '
' | sed 's/\n/
/g'
🎉 Hooray! You’re running Generative AI. Our goal is to make this as easy as possible.
Orca Mini is a family of Llama and Llama 2 models trained on datasets inspired by the methodology in the paper, Orca: Progressive Learning from Complex Explanation Traces of GPT-4. These models are designed for efficient fine-tuning and use, available in two variations: the original Orca Mini based on Llama with 3, 7, and 13 billion parameters, and Orca Mini v3 based on Llama 2 with 7, 13, and 70 billion parameters.
3B model: Pankaj Mathur
7B model: Pankaj Mathur
13B model: Pankaj Mathur
13B v3: Pankaj Mathur
70B v3: Pankaj Mathur
Orca: Progressive Learning from Complex Explanation Traces of GPT-4
DETAILS
MAX Models are extremely optimized inference pipelines to run SOTA performance for that model on both CPU and GPU. For many of these models, they are the fastest version of this model in the world.
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pankajmathur
MODEL
pankajmathur/orca_mini_v9_7_3B-Instruct
TAGS
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