Update README.md

README.md

@@ -2,29 +2,22 @@
 license: apache-2.0
 pipeline_tag: image-to-text
 ---
-# Model Card for Model ID
 
-Trained on the MIMIC-CXR chest x-rays.
+## generate-cxr
 
-
-
-# Model Details
-
-## Model Description
-
-This model generates realistic radiology reports given an chest X-ray and a clinical indication (e.g. 'RLL crackles, eval for pneumonia').
+This BlipForConditionalGeneration model generates realistic radiology reports given an chest X-ray and a clinical indication (e.g. 'RLL crackles, eval for pneumonia').
 
 - **Developed by:** Nathan Sutton
 - **Model type:** BLIP
 - **Language(s) (NLP):** English
 - **License:** Apache 2.0
-- **Finetuned from model [optional]:** Salesforce/blip-image-captioning-large
+- **Finetuned from model:** Salesforce/blip-image-captioning-large
 
-## Model Sources [optional]
+## Model SourceS
 
 - **Repository:** https://github.com/nathansutton/prerad
-- **Paper [optional]:** https://medium.com/me/stats/post/b687a993cbb
-- **Demo [optional]:** https://medium.com/me/stats/post/b687a993cbb
+- **Paper:** https://medium.com/@nasutton/a-new-generative-model-for-radiology-b687a993cbb
+- **Demo:** https://nathansutton-prerad.hf.space/
 
 
 ## Direct Use
@@ -64,6 +57,4 @@ report = processor.decode(output[0], skip_special_tokens=True)
 
 # Training Details
 
-## Training Data
-
 This model was trained by cross-referencing the radiology reports in MIMIC-CXR with the images in the MIMIC-CXR-JPG.  None are available here and require a data usage agreement with physionet.