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* sampling : one sequence per sampling context ggml-ci * speculative : add tree-based sampling support ggml-ci * speculative : reuse the n_parallel CLI param * speculative : refactor sampling * examples : fix build after sampling refactoring ggml-ci * batched : fix n_seq_id * sampling : fix malloc ggml-ci * swift : fix build ggml-ci * swift : try to fix build ggml-ci * prompts : add assistant.txt * common : add llama_batch_add() and llama_batch_clear() helpers * speculative : minor refactor ggml-ci * minor : comments + rename ggml-ci * speculative : fix off-by-one for n_drafted * speculative : fix the n_drafted fix + p constants |
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| .. | ||
| CMakeLists.txt | ||
| infill.cpp | ||
| README.md | ||
llama.cpp/example/infill
This example shows how to use the infill mode with Code Llama models supporting infill mode. Currently the 7B and 13B models support infill mode.
Infill supports most of the options available in the main example.
For further information have a look at the main README.md in llama.cpp/example/main/README.md
Common Options
In this section, we cover the most commonly used options for running the infill program with the LLaMA models:
-m FNAME, --model FNAME: Specify the path to the LLaMA model file (e.g.,models/7B/ggml-model.bin).-i, --interactive: Run the program in interactive mode, allowing you to provide input directly and receive real-time responses.-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.-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.
Input Prompts
The infill program provides several ways to interact with the LLaMA models using input prompts:
--in-prefix PROMPT_BEFORE_CURSOR: Provide the prefix directly as a command-line option.--in-suffix PROMPT_AFTER_CURSOR: Provide the suffix directly as a command-line option.--interactive-first: Run the program in interactive mode and wait for input right away. (More on this below.)
Interaction
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
Interaction Options
-i, --interactive: Run the program in interactive mode, allowing users to get real time code suggestions from model.--interactive-first: Run the program in interactive mode and immediately wait for user input before starting the text generation.--color: Enable colorized output to differentiate visually distinguishing between prompts, user input, and generated text.
Example
./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 "