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Back to milvlg/prophet

Open-source alternatives to Prophet

30 open-source projects similar to milvlg/prophet, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Prophet alternative.

  • alirezadir/machine-learning-interviewsalirezadir 的头像

    alirezadir/Machine-Learning-Interviews

    8,455在 GitHub 上查看↗

    This project is a comprehensive machine learning interview guide and technical study resource designed for individuals preparing for machine learning and AI engineering roles. It provides a collection of materials and practice problems covering core algorithms, theoretical fundamentals, and the implementation of neural network architectures. The resource serves as a technical reference for generative AI development, focusing on the design and optimization of large language models and diffusion systems. It includes frameworks for system design, covering the architecture of production machine l

    Jupyter Notebookagenticaiai-agents
    在 GitHub 上查看↗8,455
  • allenai/beaconallenai 的头像

    allenai/beacon

    14在 GitHub 上查看↗

    This repository contains code to run the inference and evaluation of NER as described in our NAACL 2024 paper: On-the-fly Definition Augmentation of LLMs for Biomedical NER

    Python
    在 GitHub 上查看↗14
  • allenai/visprogallenai 的头像

    allenai/visprog

    773在 GitHub 上查看↗

    Official code for VisProg (CVPR 2023 Best Paper!)

    Python
    在 GitHub 上查看↗773
  • artpli/codeieartpli 的头像

    artpli/CodeIE

    41在 GitHub 上查看↗

    This is the official repository for "CodeIE: Large Code Generation Models are Better Few-Shot Information Extractors" (ACL 2023).

    Python
    在 GitHub 上查看↗41

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  • baaivision/emubaaivision 的头像

    baaivision/Emu

    1,775在 GitHub 上查看↗

    Emu Series: Generative Multimodal Models from BAAI

    Python
    在 GitHub 上查看↗1,775
  • chen700564/metaner-iclchen700564 的头像

    chen700564/metaner-icl

    40在 GitHub 上查看↗

    An implementation for ACL 2023 paper Learning In-context Learning for Named Entity Recognition

    Python
    在 GitHub 上查看↗40
  • ej0cl6/texteeej0cl6 的头像

    ej0cl6/TextEE

    60在 GitHub 上查看↗

    Updates | Datasets | Models | Environment | Running | Results | Website | Paper

    Python
    在 GitHub 上查看↗60
  • emma1066/self-improve-zero-shot-nerEmma1066 的头像

    Emma1066/Self-Improve-Zero-Shot-NER

    53在 GitHub 上查看↗

    This is the github repository for the paper to be appeared at NAACL 2024 main conference: Self-Improving for Zero-Shot Named Entity Recognition with Large Language Models.

    Python
    在 GitHub 上查看↗53
  • haozhezhao/micHaozheZhao 的头像

    HaozheZhao/MIC

    360在 GitHub 上查看↗

    MMICL, a state-of-the-art VLM with the in context learning ability from ICL, PKU

    Python
    在 GitHub 上查看↗360
  • isekai-portal/link-context-learningisekai-portal 的头像

    isekai-portal/Link-Context-Learning

    101在 GitHub 上查看↗

    Zhao Zhang 3   Ziwei Liu &#x2709,1 1 S-Lab, Nanyang Technological University  2 Shanghai Jiao Tong University  3 SenseTime Research  4 Ningbo Institute of Digital Twin, Eastern Institute of Technology, Ningbo, China   Equal Contribution  † Project Lead …

    Python
    在 GitHub 上查看↗101
  • jiangguochaogg/p-icljiangguochaoGG 的头像

    jiangguochaoGG/P-ICL

    7在 GitHub 上查看↗

    Please save your dataset in data folder. Note that CoNLL2003 and WNUT2017 are open-source datasets, ACE2004 and ACE2005 are not free. We keep our CoNLL2003 and WNUT2017 train and test JSON files in data folder.

    Python
    在 GitHub 上查看↗7
  • lfoppiano/matsci-lumenlfoppiano 的头像

    lfoppiano/MatSci-LumEn

    10在 GitHub 上查看↗

    Code, data, and results described in the paper "Mining experimental data from materials science literature with large language models: an evaluation study", https://www.tandfonline.com/doi/full/10.1080/27660400.2024.2356506

    Python
    在 GitHub 上查看↗10
  • luodian/otterLuodian 的头像

    Luodian/Otter

    3,410在 GitHub 上查看↗

    🦦 Otter, a multi-modal model based on OpenFlamingo (open-sourced version of DeepMind's Flamingo), trained on MIMIC-IT and showcasing improved instruction-following and in-context learning ability.

    Python
    在 GitHub 上查看↗3,410
  • lupantech/chameleon-llmlupantech 的头像

    lupantech/chameleon-llm

    1,140在 GitHub 上查看↗

    Codes for "Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models".

    Jupyter Notebook
    在 GitHub 上查看↗1,140
  • maehcm/icl-d3ieMAEHCM 的头像

    MAEHCM/ICL-D3IE

    54在 GitHub 上查看↗

    Code for ICCV 2023 Paper : “ICL-D3IE: In-Context Learning with Diverse Demonstrations Updating for Document Information Extraction”

    Python
    在 GitHub 上查看↗54
  • mayubo2333/llm-iemayubo2333 的头像

    mayubo2333/LLM-IE

    47在 GitHub 上查看↗

    This is the implementation of filter-then-rerank pipeline in Large Language Model Is Not a Good Few-shot Information Extractor, but a Good Reranker for Hard Samples!. EMNLP'2023 (Findings).

    Python
    在 GitHub 上查看↗47
  • microsoft/jarvismicrosoft 的头像

    microsoft/JARVIS

    24,854在 GitHub 上查看↗

    JARVIS is a system for large language model task orchestration, deployment management, and automation benchmarking. It utilizes a task orchestrator to decompose complex requests into actionable steps and coordinates various expert models to synthesize final responses. The project includes an AI model deployment manager to handle the local deployment of expert models across different hardware scales. It further provides an AI workflow API consisting of web endpoints used to trigger automated task workflows and retrieve results from model selection stages. The framework incorporates an automat

    Python
    在 GitHub 上查看↗24,854
  • microsoft/mm-reactmicrosoft 的头像

    microsoft/MM-REACT

    966在 GitHub 上查看↗

    Official repo for MM-REACT

    Python
    在 GitHub 上查看↗966
  • microsoft/picamicrosoft 的头像

    microsoft/PICa

    87在 GitHub 上查看↗

    An Empirical Study of GPT-3 for Few-Shot Knowledge-Based VQA, AAAI 2022 (Oral)

    Python
    在 GitHub 上查看↗87
  • oezyurty/replmO

    oezyurty/REPLM

    0在 GitHub 上查看↗

    The original implementation of the paper. You can cite the paper as below.

    在 GitHub 上查看↗0
  • osu-nlp-group/qa4reOSU-NLP-Group 的头像

    OSU-NLP-Group/QA4RE

    40在 GitHub 上查看↗

    Data and code for ACL 2023 Findings: Aligning Instruction Tasks Unlocks Large Language Models as Zero-Shot Relation Extractors.

    Python
    在 GitHub 上查看↗40
  • shuhewang1998/gpt-nerS

    ShuheWang1998/GPT-NER

    0在 GitHub 上查看↗

    This repo contains code for the paper GPT-NER: Named Entity Recognition via Large LanguageModels. ``latex @article{wang2023gpt, title={GPT-NER: Named Entity Recognition via Large Language Models}, author={Wang, Shuhe and Sun, Xiaofei and Li, Xiaoya and Ouyang, Rongbin and Wu, Fei and Zhang,…

    在 GitHub 上查看↗0
  • snap-stanford/med-flamingosnap-stanford 的头像

    snap-stanford/med-flamingo

    451在 GitHub 上查看↗

    This is the code repo for the Med-Flamingo paper.

    Python
    在 GitHub 上查看↗451
  • tangxuemei1995/chisiectangxuemei1995 的头像

    tangxuemei1995/CHisIEC

    22在 GitHub 上查看↗

    CHisIEC: An Information Extraction Corpus for Ancient Chinese History

    C++
    在 GitHub 上查看↗22
  • toneli/rt-retrieving-and-thinkingToneLi 的头像

    ToneLi/RT-Retrieving-and-Thinking

    11在 GitHub 上查看↗

    This is the source code of the model RT (Retrieving and Thinking). For the full project, please check the file RTBC5CDR/3RT and RTNCBI/3RT, the implementation of GPT-NER and PromptNER is in the BC5CDR.zip and NCBI.zip. we refer to the source of code of GPT-NER and paper of GPT-NER in our project…

    Python
    在 GitHub 上查看↗11
  • tricktreat/promptnertricktreat 的头像

    tricktreat/PromptNER

    100在 GitHub 上查看↗

    Code for PromptNER: Prompt Locating and Typing for Named Entity Recognition, accepted at ACL 2023.

    Python
    在 GitHub 上查看↗100
  • uw-madison-lee-lab/cobsatUW-Madison-Lee-Lab 的头像

    UW-Madison-Lee-Lab/CoBSAT

    48在 GitHub 上查看↗

    Implementation and dataset for paper "Can MLLMs Perform Text-to-Image In-Context Learning?"

    Jupyter Notebook
    在 GitHub 上查看↗48
  • xingyaoww/code4structxingyaoww 的头像

    xingyaoww/code4struct

    43在 GitHub 上查看↗

    Official repo for paper Code4Struct: Code Generation for Few-Shot Structured Prediction from Natural Language.

    HTML
    在 GitHub 上查看↗43
  • yfr718/ltnerYFR718 的头像

    YFR718/LTNER

    7在 GitHub 上查看↗

    Large Language Model Tagging for Named Entity Recognition with Contextualized Entity Marking

    Python
    在 GitHub 上查看↗7
  • yongliang-wu/explorecfgyongliang-wu 的头像

    yongliang-wu/ExploreCfg

    47在 GitHub 上查看↗

    NeurIPS2023 Exploring Diverse In-Context Configurations for Image Captioning

    Python
    在 GitHub 上查看↗47