Instructions to use Arabic-Clip-Archive/m-bert-base-ViT-B-32-trained-mclip-data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Arabic-Clip-Archive/m-bert-base-ViT-B-32-trained-mclip-data with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Arabic-Clip-Archive/m-bert-base-ViT-B-32-trained-mclip-data")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Arabic-Clip-Archive/m-bert-base-ViT-B-32-trained-mclip-data") model = AutoModel.from_pretrained("Arabic-Clip-Archive/m-bert-base-ViT-B-32-trained-mclip-data", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Check out the documentation for more information.
The following checkpoint is for m-bert-base-ViT-B-32 trained on mclip dataset ( with try and execept)
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