Image-to-Text
Transformers
PyTorch
TensorBoard
vision-encoder-decoder
image-text-to-text
Generated from Trainer
Instructions to use larabe/testt1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use larabe/testt1 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "image-to-text" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("image-to-text", model="larabe/testt1")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("larabe/testt1") model = AutoModelForImageTextToText.from_pretrained("larabe/testt1") - Notebooks
- Google Colab
- Kaggle
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README.md
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model-index:
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results: []
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---
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- Transformers 4.30.1
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- Pytorch 2.0.1+cu117
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- Datasets 2.14.0
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- Tokenizers 0.13.3
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model-index:
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results: []
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pipeline_tag: image-to-text
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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- Transformers 4.30.1
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- Pytorch 2.0.1+cu117
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- Datasets 2.14.0
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- Tokenizers 0.13.3
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