Image-to-Text
Transformers
Safetensors
English
medical
pathology
vision-language
contrastive-learning
fine-grained
multimodal
Instructions to use jshhhh/PathFLIP with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jshhhh/PathFLIP 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="jshhhh/PathFLIP")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("jshhhh/PathFLIP", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 285416e53760ec37fc3a96099e4368c002cf9b7133e365304b8e5ded796fbf2d
- Size of remote file:
- 276 MB
- SHA256:
- 011f90cd4d031066a9d807cca0926bcc89e4cfbb8d4b9260d8d07a60afd48c9b
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