Instructions to use daniyal214/finetuned-git-large-chest-xrays with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use daniyal214/finetuned-git-large-chest-xrays 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="daniyal214/finetuned-git-large-chest-xrays")# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("daniyal214/finetuned-git-large-chest-xrays") model = AutoModelForMultimodalLM.from_pretrained("daniyal214/finetuned-git-large-chest-xrays", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 865669ac18cba47d58986d0a29ef59e85e4fe920239e60c412212c71b36ee3cb
- Size of remote file:
- 1.58 GB
- SHA256:
- a0fb1d1ce58ee1b6d9ce55564fb557752ff55763969e8ad584a1c52217133a0d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.