Instructions to use davanstrien/clip-roberta-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use davanstrien/clip-roberta-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="davanstrien/clip-roberta-finetuned")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModel processor = AutoProcessor.from_pretrained("davanstrien/clip-roberta-finetuned") model = AutoModel.from_pretrained("davanstrien/clip-roberta-finetuned", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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update model card README.md
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README.md
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---
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tags:
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- generated_from_trainer
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model-index:
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- name: clip-roberta-finetuned
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results: []
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# clip-roberta-finetuned
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This model
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## Model description
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---
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tags:
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- generated_from_trainer
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datasets:
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- davanstrien/manuscript_noisy_labels_iiif
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model-index:
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- name: clip-roberta-finetuned
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results: []
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# clip-roberta-finetuned
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This model is a fine-tuned version of [./clip-roberta](https://huggingface.co/./clip-roberta) on the davanstrien/manuscript_noisy_labels_iiif dataset.
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## Model description
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