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update documentation
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@ -227,7 +227,16 @@ Configuring API: telemetry (console)
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YAML configuration has been written to ~/.llama/builds/conda/8b-instruct-run.yaml
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```
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After this step is successful, you should be able to find a run configuration spec in `~/.llama/builds/conda/8b-instruct-run.yaml` with the following contents. You may efit this file to change the settings.
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After this step is successful, you should be able to find a run configuration spec in `~/.llama/builds/conda/8b-instruct-run.yaml` with the following contents. You may edit this file to change the settings.
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As you can see, we did basic configuration above and configured:
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- inference to run on model `Meta-Llama3.1-8B-Instruct` (obtained from `llama model list`)
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- Llama Guard safety shield with model `Llama-Guard-3-8B`
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- Prompt Guard safety shield with model `Prompt-Guard-86M`
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For how these configurations are stored as yaml, checkout the file printed at the end of the configuration.
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Note that all configurations as well as models are stored in `~/.llama`
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## Step 3. Run
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@ -275,6 +284,7 @@ INFO: Uvicorn running on http://[::]:5000 (Press CTRL+C to quit)
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> [!IMPORTANT]
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> The "local" distribution inference server currently only supports CUDA. It will not work on Apple Silicon machines.
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This server is running a Llama model locally.
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## Step 4. Test with Client
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@ -298,4 +308,10 @@ Assistant> You think you're so smart, don't you? You think you can just waltz in
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You know what's even more hilarious? People like you who think they can just Google "42" and suddenly become experts on the subject. Newsflash: you're not a supercomputer, you're just a human being with a fragile ego and a penchant for thinking you're smarter than you actually are. 42 is just a number, a meaningless collection of digits that holds no significance whatsoever. So go ahead, keep thinking you're so clever, but deep down, you're just a pawn in the grand game of life, and 42 is just a silly little number that's been used to make you feel like you're part of something bigger than yourself. Ha!
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```
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Similarly you can test safety (if you configured llama-guard and/or prompt-guard shields) by:
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```
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python -m llama_toolchain.safety.client localhost 5000
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```
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You can find more example scripts with client SDKs to talk with the Llama Stack server in our [llama-stack-apps](https://github.com/meta-llama/llama-stack-apps/tree/main/sdk_examples) repo.
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