LLM Benchmark for Throughput via Ollama (Local LLMs) Installation prerequisites Working Ollama installation. Installation Steps Depending on your python setup either pip install llm-benchmark or pipx install llm-benchmark Usage for general users directly llm_benchmark run Installation and Usage in ...
pip install -r requirements.txt export OPENAI_API_KEY="[your_openai_api_key]" 步骤2. 下载数据 你可以通过Hugging Face数据集下载和加载LooGLE数据(�� HF Repo): from datasets import load_dataset datasets = ["shortdep_qa", "shortdep_cloze", "longdep_qa", "longdep_summarization"] for t...
cd opencompass pip install -e . # 如果需要使用各个API模型,请 `pip install -r requirements/api.txt` 安装API模型的相关依赖 📂 数据准备 # 下载数据集到 data/ 处 wget https://github.com/open-compass/opencompass/releases/download/0.2.2.rc1/OpenCompassData-core-20240207.zip unzip OpenCompassDat...
Prepare for CLI (typer) and pip install Mar 28, 2024 run_benchmark.py add in flag --ollamabin to explicitly give the path to the ollama exe… Apr 3, 2024 run_benchmark_one.py Prepare for CLI (typer) and pip install Mar 28, 2024...
$ git clone https://github.com/kingabzpro/human-eval$ pip install-e human-eval$ evaluate_functional_correctness data/example_samples.jsonl--problem_file=data/example_problem.jsonl We got the result in terms of pass@k, and, in our case, pass@1. This metric indicates a model's 50% suc...
pip install -e . # 如果需要使用各个API模型,请 `pip install -r requirements/api.txt` 安装API模型的相关依赖 📂 数据准备 # 下载数据集到 data/ 处 wget https://github.com/open-compass/opencompass/releases/download/0.2.2.rc1/OpenCompassData-core-20240207.zip ...
pip install -r requirements.txt export OPENAI_API_KEY="[your_openai_api_key]" 步骤2. 下载数据 你可以通过Hugging Face数据集下载和加载LooGLE数据(�� HF Repo): from datasets import load_dataset datasets = ["shortdep_qa", "shortdep_cloze", "longdep_qa", "longdep_summarization"] ...
Install the package using pip: pip install pyllms Quick Start import llms model = llms.init('gpt-4o') result = model.complete("What is 5+5?") print(result.text) Usage Basic Usage import llms model = llms.init('gpt-4o') result = model.complete( "What is the capital of the co...
pip install -r requirements.txt Configuration Create a YAML configuration file to define your test scenarios. An example of the configuration structure is provided below: model_id: meta-llama/Meta-Llama-3-8B-Instruct num_gpus: 1 memory_per_gpu: 24 tgi: max_batch_prefill_tokens: 6144 max_inp...
pip install -e . 我们还提供了许多可选依赖项以扩展功能。在本文件末尾有一个详细的表格。 2、基本使用 用户指南 提供了一个用户指南,详细列出了支持的所有参数,可以在此处和终端中通过调用lm_eval -h查看。或者,可以使用lm-eval代替lm_eval。 可以使用lm-eval --tasks list查看支持的任务列表(或任务分组)。