Using the large model MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7 to achieve zero-sample classification - Code World

Using the large model MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7 to achieve zero-sample classification

Enterprise 2023-09-30 02:27:28 views: null

NoSuchKey

Guess you like

Origin blog.csdn.net/duzm200542901104/article/details/132676457

Using the large model MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7 to achieve zero-sample classification

Fine-tuning the deberta-v3-large model for text classification using the emotion dataset

Dify Tutorial 2: Using a Local Large Model

SeaFormer combat: using SeaFormer to achieve image classification tasks (2)

VanillaNet combat: using VanillaNet to achieve image classification (2)

DEiT combat: using DEiT to achieve image classification tasks (2)

InceptionNext combat: using InceptionNext to achieve image classification tasks (2)

MobileViG combat: using MobileViG to achieve image classification tasks (2)

FastViT combat: using FastViT to achieve image classification tasks (2)

Caffe: Classification using python script to achieve Mnist

Predicting sentiment classification using fine-tuned deberta-v3-large

Recommended GEE articles - Using the sample point migration method to quickly achieve global land classification based on Landsat images from 1984 to the present

Zero base, zero cost, deploy a large model that belongs to you

v-model custom components to achieve the principle of using the v-model

This article was automatically generated using an AI large model

[AI Language Large Model] Introduction to using Spark

Generate SQL Schema using large language model

ICLR 2023 | Research on small-sample learning and zero-sample inference performance of medical images based on visual language pre-training model

CloFormer combat: using CloFormer to achieve image classification tasks (1)

DEiT combat: using DEiT to achieve image classification tasks (1)

VanillaNet combat: using VanillaNet to achieve image classification (1)

MobileViG combat: using MobileViG to achieve image classification tasks (1)

Python: Using CNN neural network to achieve CSV data classification prediction

FasterViT combat: using FasterViT to achieve image classification tasks (1)

FastViT combat: using FastViT to achieve image classification tasks (1)

Micro Frontiers | Issue 1: Strongly Controllable Video Generation; Customized Sample Retrieval; Using EEG to Reconstruct Visual Perception; Large Model Robustness Evaluation

How to achieve gorgeous corner overtaking on a large model track

Building a system using a large language model (LLM) (3): Thinking chain reasoning

Re-using a classification CNN model for autoencoding - pytorch

Re-using a classification CNN model for autoencoding - pytorch

Recommended

Ranking

TopoGun: Shortcuts

OneFlow Study Notes: From Functor to OpExprInterpreter

Other series NRF52 contrast, low-power Bluetooth 5.2, where the advantages of Soc chip NRF52820 in?

Spring explain (b)

python in parentheses knowledge

Using dedicated clock pins

9. Appearance mode of design mode

Aidlux Industrial Vision Defect Inspection

Reptile start selenium- install Google Chrome and drive (fool tutorial) under linux

How to implement css dotted line style?

Daily

More

2025-04-15(0)

2025-04-14(0)

2025-04-13(0)

2025-04-12(0)

2025-04-11(0)

2025-04-10(0)

2025-04-09(0)

2025-04-08(0)

2025-04-07(0)

2025-04-06(0)