Upload model

README.md

@@ -1,8 +1,8 @@
 ---
 language:
 - en
-license: apache-2.0
 library_name: transformers
+license: apache-2.0
 tags:
 - chest X-ray report generation
 - radiology report generation

config.json

@@ -61,6 +61,7 @@
       "history"
     ],
     "min_length": 0,
+    "mlp_bias": false,
     "model_type": "llama",
     "no_repeat_ngram_size": 0,
     "num_attention_heads": 12,
@@ -234,9 +235,8 @@
     "typical_p": 1.0,
     "use_bfloat16": false
   },
-  "is_encoder_decoder": true,
   "model_type": "vision-encoder-decoder",
   "tie_word_embeddings": false,
   "torch_dtype": "float32",
-  "transformers_version": "4.39.0"
+  "transformers_version": "4.42.3"
 }

dataset.py

@@ -8,8 +8,6 @@ import torch
 from torch.utils.data import Dataset
 from torchvision.io import decode_image, read_image
 
-from data.mimic_cxr.dcm_processing import load_and_preprocess_dcm_uint16
-from tools.mimic_iv.ed_cxr.records import EDCXRSubjectRecords
 from tools.utils import mimic_cxr_image_path
 
 # Ordered by oblique, lateral, AP, and then PA views so that PA views are closest in position to the generated tokens (and oblique is furtherest).

generation_config.json

@@ -3,5 +3,5 @@
   "bos_token_id": 1,
   "eos_token_id": 2,
   "pad_token_id": 4,
-  "transformers_version": "4.39.0"
+  "transformers_version": "4.42.3"
 }

modelling_cxrmate_ed.py

@@ -6,7 +6,6 @@ from typing import Optional, Tuple, Union
 
 import duckdb
 import pandas as pd
-import streamlit as st
 import torch
 import transformers
 from torch.nn import CrossEntropyLoss