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42 lines
2.3 KiB
Markdown
42 lines
2.3 KiB
Markdown
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# llama.cpp/example/infill
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This example shows how to use the infill mode with Code Llama models supporting infill mode.
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Currently the 7B and 13B models support infill mode.
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Infill supports most of the options available in the main example.
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For further information have a look at the main README.md in llama.cpp/example/main/README.md
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## Common Options
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In this section, we cover the most commonly used options for running the `infill` program with the LLaMA models:
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- `-m FNAME, --model FNAME`: Specify the path to the LLaMA model file (e.g., `models/7B/ggml-model.bin`).
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- `-i, --interactive`: Run the program in interactive mode, allowing you to provide input directly and receive real-time responses.
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- `-n N, --n-predict N`: Set the number of tokens to predict when generating text. Adjusting this value can influence the length of the generated text.
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- `-c N, --ctx-size N`: Set the size of the prompt context. The default is 512, but LLaMA models were built with a context of 2048, which will provide better results for longer input/inference.
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## Input Prompts
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The `infill` program provides several ways to interact with the LLaMA models using input prompts:
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- `--in-prefix PROMPT_BEFORE_CURSOR`: Provide the prefix directly as a command-line option.
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- `--in-suffix PROMPT_AFTER_CURSOR`: Provide the suffix directly as a command-line option.
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- `--interactive-first`: Run the program in interactive mode and wait for input right away. (More on this below.)
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## Interaction
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The `infill` program offers a seamless way to interact with LLaMA models, allowing users to receive real-time infill suggestions. The interactive mode can be triggered using `--interactive`, and `--interactive-first`
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### Interaction Options
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- `-i, --interactive`: Run the program in interactive mode, allowing users to get real time code suggestions from model.
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- `--interactive-first`: Run the program in interactive mode and immediately wait for user input before starting the text generation.
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- `--color`: Enable colorized output to differentiate visually distinguishing between prompts, user input, and generated text.
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### Example
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```bash
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./infill -t 10 -ngl 0 -m models/codellama-13b.Q5_K_S.gguf -c 4096 --temp 0.7 --repeat_penalty 1.1 -n 20 --in-prefix "def helloworld():\n print(\"hell" --in-suffix "\n print(\"goodbye world\")\n "
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```
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