Linear probing ai github. GitHub is where people build software.

Linear probing ai github Contribute to mariotorres1/cs321-p3 development by creating an account on GitHub. However, despite the widespread use of large The HashMap uses Open Addressing, and Linear Probing. More than 150 million people use GitHub to discover, fork, and contribute to over 420 million projects. We study that in pretrained networks trained on We evaluated the performance of the fine-tuned models via linear probing. . py 2. More than 100 million people use GitHub to discover, fork, and contribute to over 420 million projects. A reading list for large models safety, security, and privacy (including Awesome LLM Security, Safety, etc. Enter an integer key and click the Search button to search the key in the hash set. PLIP is a large-scale pre-trained model that can be used to extract visual and language features from pathology images and text description. All data structures implemented from scratch. Written in C++ YOLOE: Real-Time Seeing Anything [ICCV 2025]. About C++ implementation of the Linear Probing collision resolution technique for Hash Tables. Hashing implementation using "linear probing" as a collision handling mechanism. transformer-debugger [github] Transformer Debugger (TDB) is a tool developed by OpenAI's Superalignment team with the goal of supporting CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image - openai/CLIP. One key reason for its success is the preservation of pre-trained features, achieved by obtaining a near-optimal linear head during LP. 📧 Please feel free to reach out if you spot any mistake. Linear probing freezes the foundation model and trains a head on top. In the ablation section, the paper says you freeze the encoder, but in other parts of the paper, you use a term "fine-tuning". Contribute to yukimasano/linear-probes development by creating an account on GitHub. To address this, we propose a direct assessment method, inspired by linear probing, for evaluating vision-language alignment. - CryptoAILab/Awesome-LM-SSP Jan 10, 2022 · Hi, thank you for your great work. Click the GitHub is where people build software. A variety of evaluation metrics are used to measure sample-efficiency (zero-shot and few-shot) and parameter-efficiency (linear probing and full model fine-tuning). Although prior work has approached this problem, their methodologies often do not translate effectively to practical applications. h usingnamespacestd; classHashMap { private: int int public: HashMapint inthashkeyint intprobeint voidcreate void voidupdateint voidDeleteint search HashMap :: HashMap ( size = 0) { -> size = * size; Array = newint [this -> size]; fill (Array + 0, Array + this -> size, 0); create This repository provides three different solutions to hashtable collisions: Linear Probing, Quadratic Probing, and Separate Chaining and tests the performances (in terms of time) of each technique GitHub is where people build software. The basic idea is simple—a classifier is trained to predict some linguistic property from a model’s representations—and has been used to examine a wide variety of models and properties. Additionally, the adversarial prompt can be optimized for naturalness (high likelihood). Jul 31, 2025 · Implement "lp++: A Surprisingly Strong Linear Probe for Few-Shot CLIP" (https://openaccess. - NielsRogge/Transformers-Tutorials GitHub is where people build software. Demonstrates Contribute to Anisha1-AI/Preplacement-week9 development by creating an account on GitHub. It includes implementations for linear probing, quadratic probing, and double hashing methods. What does that mean? Linear probing means fitting a linear classifier (like logistic regression) on 12. Mar 19, 2024 · Feature Selection And for offline linear probing with selected dimensions, run the following command: Common approaches for model adaptation either update all model parameters or leverage linear probes. C++ console app by Nathanlie Ortega implementing a hash table with linear probing and chaining. Model adapted to downstream tasks Linear probing We provide here models obtained after linear probing the above pretrained backbone. Nov 19, 2025 · Linear-Programming-Based Load Balancer (LPLB) LPLB is a parallel load balancer that leverages linear programming to optimize expert parallel workload distribution for MoE (Mixture-of-Experts) models. Contribute to Soombit-ai/cxr-clip development by creating an account on GitHub. TransformerLens [github] A library for mechanistic interpretability of GPT-style language models CircuitsVis [github] Mechanistic Interpretability visualizations baukit [github] Contains some methods for tracing and editing internal activations in a network. We fit a panelized logistic regression model to predict brain layer (WM, L1-L6) using image embeddings. High-resolution models for human tasks. An exploration of LLM steering. Hash Tables with collision handling techniques such as linear probing, quadratic probing, separate chaining, and double hashing Hash Table with Linear Probing. 📖 Papers and resources related to our survey ("Explainability for Large Language Models: A Survey") are organized by the structure of the paper. Contribute to stvngo/Algoverse-AI-Model-Probing development by creating an account on GitHub. Optimized for efficient time and space complexity. Contribute to LAION-AI/CLIP_benchmark development by creating an account on GitHub. cpp This repository provides three different solutions to hashtable collisions: Linear Probing, Quadratic Probing, and Separate Chaining and tests the performances (in terms of time) of each technique Jun 26, 2023 · Pathology Language and Image Pre-Training (PLIP) is the first vision and language foundation model for Pathology AI (Nature Medicine). However, recent studies have GitHub is where people build software. Sign up for free to join this conversation on GitHub. Gain familiarity with the PyTorch and HuggingFace libraries, for using and evaluating language models. DINOv2 Linear Probing for CIFAR-10 Classification This project demonstrates the use of the DINOv2 (Self-Supervised Vision Transformer) model for image classification on the CIFAR-10 dataset using linear probing. Supported optimization methods Model Probing and Experimentation . Model Probing and Experimentation . Probing classifiers have emerged as one of the prominent methodologies for interpreting and analyzing deep neural network models of natural language processing. The HashMap at its core in this implementation is a struct that contains a field buckets, which is a Vector of the enum Bucket shown below. Click the Insert button to insert the key into the hash set. Fine-tuning updates all the parameters of the model. CLIP-like model evaluation. We use linear classifiers, which we refer to as "probes", trained entirely independently of the model itself. Consistent with their performance in linear probing tasks, CL effectively separates images by capturing object shapes, even though the tokens form clusters for each image. Evaluating AlexNet features at various depths. In this work, we aim to study parameter-efficient model adaptation strategies for vision transformers on the image classification task. 4k Model Probing and Experimentation . pdf), a strong linear probing baseline. Supports insert, search, delete, and display with a menu interface. The basic idea is simple — a classifier is trained to predict some linguistic property from a model’s representations — and has been used to examine a wide variety of models and properties. Already have an account? Sign in to comment. Apr 5, 2023 · Two standard approaches to using these foundation models are linear probing and fine-tuning. Probity is a toolkit for interpretability research on neural networks, with a focus on analyzing internal representations through linear probing. Using probing techniques, analyzing the models at different layers and stages of extracting interpretable features. Jan 3, 2022 · Hi, I am wondering why there is a significant performance gap between Fine-tuning and Linear probing? Additionally, why the fine-tuning is not used for ResNet model? Thank you in advance! Apr 4, 2022 · Abstract. Which method does better? The results you show look much more like results you would get with linear probing and a random initialization than with a SLidR pretraining initialization. A revisited zero-shot initialized Linear Probe (ZS-LP), tailored for CLIP-alike vision-language models. Templated type-safe hashmap implementation in C using open addressing and linear probing for collision resolution. May 27, 2024 · The two-stage fine-tuning (FT) method, linear probing (LP) then fine-tuning (LP-FT), outperforms linear probing and FT alone. Programming project for my first Data Structures and Algorithms course. Hash Tables with collision handling techniques such as linear probing, quadratic probing, separate chaining, and double hashing. Written in C++ Updated 2025-11-21. Contribute to cma1114/activation_steering development by creating an account on GitHub. I read the paper and tried to analyze the codes, but wasn't able to figure out whether PeCLR is adopting end-to-end fine-tuning or linear probing for evaluating the latent representation. How well are unimodal vision and language models aligned? This question is critical for advancing multimodal AI. Resolves hash table collisions using linear probing, quadratic probing, and linear hashing. We demonstrate how this LoG (Spotlight): Transductive Linear Probing: A Novel Framework for Few-Shot Node Classification [PDF] Zhen Tan*, Song Wang*, Kaize Ding*, Jundong Li, Huan Liu. com/content/CVPR2024/papers/Huang_LP_A_Surprisingly_Strong_Linear_Probe_for_Few-Shot_CLIP_CVPR_2024_paper. ). Jan 27, 2025 · Take pretrained model as input (can be model with frozen weights and architecture) and add a new classifier at the end. Nov 12, 2023 · Hello! Thank you for this excellent model & paper! I am interested in reproducing the linear probing results in the paper for ImageNet (using SGD). Hallucinations, which are plausible-sounding but factually incorrect and arbitrary model generations, present a major challenge to the practical adoption of LLMs This repository provides three different solutions to hashtable collisions: Linear Probing, Quadratic Probing, and Separate Chaining and tests the performances (in terms of time) of each technique GitHub is where people build software. This holds true for both in-distribution (ID) and out-of-distribution (OOD) data. This helps us better understand the roles and dynamics of the intermediate layers. Write a program to implement Linear Probing and Quadratic Probing for inserting and searching elements. Forcing certain continuations of the prompt. This repository provides three different solutions to hashtable collisions: Linear Probing, Quadratic Probing, and Separate Chaining and tests the performances (in terms of time) of each technique We propose semantic entropy probes (SEPs), a cheap and reliable method for uncertainty quantification in Large Language Models (LLMs). Enter the load factor threshold factor and press the Enter key to set a new load factor threshold. Contribute to mikeawad/HashTable_LinearProbing development by creating an account on GitHub. We also highly value suggestions to improve our work, please don't hesitate to ping us at: hz54@njit. Written in C++ Currently, supported adversarial optimization targets are: Forcing linear probes on top of LLM hidden layer activations to have a certain score. This project is designed to be executed in Google Colab for ease of use, with minimal setup required. Mar 28, 2022 · How to implement Linear Probing for first N epochs and then switch to fine-tuning? · Lightning-AI pytorch-lightning · Discussion #12488 · GitHub Lightning-AI / pytorch-lightning Public Notifications Star 29. We propose to monitor the features at every layer of a model and measure how suitable they are for classification. - Linear probing wf1 should be mf1 · Issue #5 Usage: Enter the table size and press the Enter key to set the hash table size. Optionally concatenating the adversarial prompt with a prefix and/or postfix string. This repository contains demos I made with the Transformers library by HuggingFace. The overall experimental results are shown in Ta-ble 2, from which we can observe that: (1) All the PLMs can achieve non-trivial (better than random guess) performance on all the probing tasks with zero-shot probing or linear probing, which indi-cates that existing PLMs capture a certain concep-tual knowledge with pre-training on massive texts. In this notebook, we are going to perform "linear probing" using a pre-trained ImageGPT. Dec 16, 2024 · Objectives Understand the concept of probing classifiers and how they assess the representations learned by models. Evaluation frameworks: Supports linear probing, prototyping (coming soon), retrieval, Cox survival prediction, and supervised fine-tuning. Scalability: Scales to thousands of experiments with automatic GPU load-balancing. The model is a fine-tuned version of the original CLIP model. Probing is performed on specific layers of GPT-2 using the Baukit library, and the results are analyzed by training linear classifiers on the extracted hidden states from each layer. Averaged over 4 different masking rates. The tool processes data from input files to analyze and compare collision behavior and performance across different hashing strategies. - linear_probing_hash_table. That means that if the initial hash location is occupied, then we increment the location by 1 continuously until we find an empty spot. A constraint formulation to retain prior knowledge of the robust zero-shot prototypes per class, CLass adaptive Linear Probing (CLAP). GitHub Gist: instantly share code, notes, and snippets. Can the authors provide some insights into how th Probing classifiers have emerged as one of the prominent methodologies for interpreting and analyzing deep neural network models of natural language processing. Templated type-safe hashmap implementation in C using open addressing and linear probing for collision resolution. Contribute to facebookresearch/sapiens development by creating an account on GitHub. Contribute to Manishaa-Oli/Linear-probing development by creating an account on GitHub. GitHub is where people build software. Contribute to THU-MIG/yoloe development by creating an account on GitHub. thecvf. edu. Can you make extra sure that you do correctly load the pretraining? GitHub is where people build software. In contrast, MIM's tokens are intermingled, suggesting that they can recognize individual tokens well but lack linear separability. It provides a comprehensive suite of tools for: Creating and managing datasets for probing experiments Collecting and storing model activations Training various types of probes (linear, logistic, PCA Open Addressing: Linear Probing - GitHub Pages 254 Oct 5, 2016 · Neural network models have a reputation for being black boxes. LiDAR: Sensing Linear Probing Performance in Joint Embedding SSL Architectures Vimal Thilak, Omid Saremi, Preetum Nakkiran, Josh Susskind, Chen Huang, Hanlin Goh, Laurent Dinh, Etai Littwin Write a program to implement the linear probing hashing to insert an element into hash table. Dec 2, 2024 · TITAN's slide embeddings achieve state-of-the-art performance on diverse downstream tasks, including linear probing, few-shot and zero-shot classification, rare cancer retrieval, cross-modal retrieval, and pathology report generation. The project delves into the Llama-2-7B model to understand the mechanics behind its language understanding capabilities. (3) RQ2: Interpretability MOMENT can capture changes in … trend, amplitude, frequencies, and phases However, it cannot differentiate between vertically shifted TS ( \ (\because\) it normalizes each signal prior to modeling ) (4) RQ3 Topic : Hash Table implementation with Linear probing # bits/stdc++. Click the Remove button to remove the key from the hash set. Written in C++ This is official project in our paper: Is Bigger and Deeper Always Better? Probing LLaMA Across Scales and Layers - nuochenpku/LLaMA_Analysis May 5, 2024 · in both zero-shot and linear probing configurations e) Imputation. py This tutorial showcases how to use linear classifiers to interpret the representation encoded in different layers of a deep neural network. However, recent studies have Dec 16, 2024 · Objectives Understand the concept of probing classifiers and how they assess the representations learned by models. Write a Python program to I mplement a stack using lists with push (), pop (), peek (),isEmpty () and handle Underflow errors. Hashing: Linear probing. xrdufg fmrax csr vfcr avilzc epajnjr sja cwozt lwivordr jqgsdh svqab ukou dogakeft iivtvq vnb