Spaces:
Running
Running
# Low-Level API for Llama_cpp | |
## Overview | |
This Python script, low_level_api_llama_cpp.py, demonstrates the implementation of a low-level API for interacting with the llama_cpp library. The script defines an inference that generates embeddings based on a given prompt using .gguf model. | |
### Prerequisites | |
Before running the script, ensure that you have the following dependencies installed: | |
. Python 3.6 or higher | |
. llama_cpp: A C++ library for working with .gguf model | |
. NumPy: A fundamental package for scientific computing with Python | |
. multiprocessing: A Python module for parallel computing | |
### Usage | |
install depedencies: | |
```bash | |
python -m pip install llama-cpp-python ctypes os multiprocessing | |
``` | |
Run the script: | |
```bash | |
python low_level_api_llama_cpp.py | |
``` | |
## Code Structure | |
The script is organized as follows: | |
### . Initialization: | |
Load the model from the specified path. | |
Create a context for model evaluation. | |
### . Tokenization: | |
Tokenize the input prompt using the llama_tokenize function. | |
Prepare the input tokens for model evaluation. | |
### . Inference: | |
Perform model evaluation to generate responses. | |
Sample from the model's output using various strategies (top-k, top-p, temperature). | |
### . Output: | |
Print the generated tokens and the corresponding decoded text. | |
### .Cleanup: | |
Free resources and print timing information. | |
## Configuration | |
Customize the inference behavior by adjusting the following variables: | |
#### . N_THREADS: Number of CPU threads to use for model evaluation. | |
#### . MODEL_PATH: Path to the model file. | |
#### . prompt: Input prompt for the chatbot. | |
## Notes | |
. Ensure that the llama_cpp library is built and available in the system. Follow the instructions in the llama_cpp repository for building and installing the library. | |
. This script is designed to work with the .gguf model and may require modifications for compatibility with other models. | |
## Acknowledgments | |
This code is based on the llama_cpp library developed by the community. Special thanks to the contributors for their efforts. | |
## License | |
This project is licensed under the MIT License - see the LICENSE file for details. |