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AmrSheta
/

Meme

Text Classification

feature-extraction

Model card Files Files and versions

Instructions to use AmrSheta/Meme with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AmrSheta/Meme with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-classification", model="AmrSheta/Meme")

# Load model directly
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("AmrSheta/Meme")
model = AutoModel.from_pretrained("AmrSheta/Meme")

Notebooks
Google Colab
Kaggle

How to use from the

Use from the

Transformers library

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-classification", model="AmrSheta/Meme")

# Load model directly
from transformers import AutoTokenizer, AutoModel

tokenizer = AutoTokenizer.from_pretrained("AmrSheta/Meme")
model = AutoModel.from_pretrained("AmrSheta/Meme")

Quick Links

Read model documentation
Read docs on high-level-pipeline
Read our learning resources

#meme description classification

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