| ## Run benchmark | |
| ### Benchmark sglang | |
| ``` | |
| python3 -m sglang.launch_server --model-path codellama/CodeLlama-7b-instruct-hf --port 30000 | |
| ``` | |
| ``` | |
| python3 bench_sglang.py --num-questions 10 --parallel 1 | |
| ``` | |
| ### Benchmark vllm | |
| ``` | |
| python3 -m vllm.entrypoints.api_server --tokenizer-mode auto --model codellama/CodeLlama-7b-instruct-hf --disable-log-requests --port 21000 --gpu 0.97 | |
| ``` | |
| ``` | |
| python3 bench_other.py --backend vllm --num-questions 64 | |
| ``` | |
| ### Benchmark guidance | |
| ``` | |
| python3 bench_other.py --backend guidance --num-questions 32 --parallel 1 --n-ctx 11000 --model-path path/to/code-llama/gguf | |
| ``` | |
| ### Build dataset | |
| ``` | |
| pip install PyPDF2 | |
| python3 build_dataset.py | |
| ``` | |
| ```python | |
| import PyPDF2 | |
| with open('llama2.pdf', 'rb') as file: | |
| reader = PyPDF2.PdfReader(file) | |
| text = '' | |
| for page_num in range(len(reader.pages)): | |
| text += reader.pages[page_num].extract_text() | |
| with open('output.txt', 'w') as text_file: | |
| text_file.write(text) | |
| ``` | |