3 个仓库
Awesome GitHub RepositoriesModel Visualization Tools
Utilities for visualizing the internal states, embeddings, and performance metrics of PyTorch models.
Distinct from PyTorch Training Frameworks: Focuses on the visual analysis of model performance and embeddings rather than the training execution framework.
Explore 3 awesome GitHub repositories matching artificial intelligence & ml · Model Visualization Tools. Refine with filters or upvote what's useful.
Awesome Model Visualization Tools GitHub Repositories
用 AI 发现最棒的仓库。我们将通过 AI 为您搜索最匹配的仓库。
- fossasia/visdom
fossasia/visdom
10,268在 GitHub 上查看Visdom is a tool for scientific experiment tracking and real-time data monitoring. It provides a programmatic interface for broadcasting live plots, rich media, and training metrics from scripts to an interactive web dashboard. The project specializes in high-dimensional data analysis, offering capabilities to project complex feature sets into 2D space using t-SNE and visualize PyTorch model embeddings. It organizes visualizations into named environments, allowing users to isolate different experimental runs and compare plots across these environments in a single view. The system covers a br
Visualizes high-dimensional embeddings and training metrics using PyTorch and Numpy to analyze model performance.
Python - david-gpu/srez
david-gpu/srez
5,271在 GitHub 上查看Srez 是一个深度学习图像超分辨率框架，旨在将低分辨率图像放大为清晰的高分辨率视觉特征。它作为一个神经网络训练工具，采用生成对抗网络（GAN）来合成逼真的图像细节。 该项目包含一个模型演化可视化器，可生成动画和图像批次，以跟踪训练过程中的视觉改进。它结合使用对抗损失和 L1 损失函数来优化模型权重，并支持定期保存状态检查点以便恢复和部署。 该系统涵盖了使用前馈层、批归一化和激活函数的神经网络构建。它还提供可观测性工具，用于将放大质量与真实数据进行对比，并通过迭代视觉序列监控训练进度。
Ships a tool that creates animations and image batches to track visual improvements during training.
Python - instruction-tuning-with-gpt-4/gpt-4-llm
Instruction-Tuning-with-GPT-4/GPT-4-LLM
4,335在 GitHub 上查看本项目是一个指令微调框架和合成数据生成器，使用高容量教师模型来生成用于训练较小学生模型的指令遵循对。它提供了用于监督指令微调和人类反馈强化学习的数据集和工具。 该框架专注于跨语言微调，提供高质量的英语和中文指令遵循示例，以提高模型在不同脚本间的泛化能力。它包括一个用于创建偏好数据集和用于训练奖励系统的比较评级的奖励建模工具。 该项目涵盖了通过偏好基准和非自然指令数据集进行的语言模型评估，以及将原始日志转换为性能图表的训练可视化。
Generates performance figures and plots from extracted training data using a notebook-based workflow.
HTMLalpacachatgptgpt-4
