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regenerate markdown with eom tags and tool role

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Suraj Subramanian 2025-04-07 11:04:34 -07:00
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6
llama_stack/models/llama/llama4/prompt_format.md
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@ -10,6 +10,7 @@ Here is a list of special tokens that are supported by Llama 4:
- at the end of a direct interaction between the model and the user
- at the end of multiple interactions between the model and any available tools
This token signals to the executor that the model has finished generating a response.
- `<|eom|>`: End of message. This tag is used with the `tool` role, and is used at the end of the response from the executor.
- `<|image_start|>` and `<|image_end|>`: These tokens enclose the image data in the prompt.
- `<|patch|>`: This token represents a piece of the tile/
- `<|tile_y_separator|>` and `<|tile_x_separator|>`: These tokens are used to separate the y and x tiles of an image
@ -17,10 +18,11 @@ Here is a list of special tokens that are supported by Llama 4:
There are 3 different roles that are supported by Llama 4
There are 4 different roles that are supported by Llama 4
- `system`: Sets the context in which to interact with the AI model. It typically includes rules, guidelines, or necessary information that helps the model respond effectively.
- `user`: Represents the human interacting with the model. It includes the inputs, commands, and questions to the model.
- `assistant`: Represents the response generated by the AI model based on the context provided in the `system`, `tool` and `user` prompts.
- `tool`: Represents the output of a tool call when sent back to the model from the executor. (The actual token used by the model is `<|ipython|>`.)
# Llama 4 Instruct Model
@ -319,3 +321,5 @@ The top 2 latest trending songs are:
- Tool outputs should be passed back to the model in the `tool` role, which uses the `<|ipython|>` tag.
- The model parses the tool output contents until it encounters the `<|eom|>` tag. It uses this to synthesize an appropriate response to the query.