2 versions
An extension of Llama 2 that supports a context of up to 128k tokens.
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 yarn-llama2/7b:
max-serve serve --huggingface-repo-id NousResearch/Yarn-Llama-2-7b-64k
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": "yarn-llama2/7b",
"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'
๐ Hooray! Youโre running Generative AI. Our goal is to make this as easy as possible.
Yarn Llama 2 is an advanced language model based on Llama2, designed to support extended context sizes of up to 128k tokens. Developed by Nous Research, it leverages the YaRN method to enhance the model's capacity for processing larger context windows. This makes it particularly suitable for tasks requiring extensive context understanding, such as long-form writing or detailed document analysis.
The model is available in configurations for 64k and 128k context sizes and can be accessed via API. Developers can use the model by submitting a prompt to generate text, showcasing its ability to handle highly contextualized input efficiently.
YaRN: Efficient Context Window Extension of Large Language Models
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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NousResearch
MODEL
NousResearch/Yarn-Llama-2-7b-64k
TAGS
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