Instructions to use nathansutton/generate-cxr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nathansutton/generate-cxr 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="nathansutton/generate-cxr")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("nathansutton/generate-cxr") model = AutoModelForMultimodalLM.from_pretrained("nathansutton/generate-cxr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model (#1)
Verified signature- Adding `safetensors` variant of this model (00b87396f324de1bdb6a0977faeb2fb1f6e29ec6) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>6609ed3
-
Update README.md
07c6d3e -
Update README.md
9ea1aa5 -
Create README.md
d656f6d
-
Upload processor
8ad1b5d -
Upload BlipForConditionalGeneration
b3bed95
-
Upload processor
371fd9a -
Upload BlipForConditionalGeneration
ac95824 -
initial commit
a1df0e4