fixed typos

README.md

@@ -41,16 +41,24 @@ How well the generated sentences adhere to FHIR standards.
 ## Usage
 Here's a simple Python code snippet to use this model:
 
-```from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+```
+  from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
   tokenizer = AutoTokenizer.from_pretrained("rapidfhir-procedures")
-  model = AutoModelForSeq2SeqLM.from_pretrained("rapidfhir-procedures")  
-  input_text = "Procedure code: 1234, Description: Appendectomy"
-  input_tokenized = tokenizer(input_text, return_tensors="pt")
-  output = model.generate(**input_tokenized)
-  output_text = tokenizer.decode(output[0], skip_special_tokens=True)  
-  print(output_text)
+  model = AutoModelForSeq2SeqLM.from_pretrained("rapidfhir-procedures")
+  prompt = "SQM9PZ2545XHC4TE9RS27V183DD9KPW6JOI53UU5NYY8XRGIW6NZ0227WOAAW6NDNO79SR2K75T6J104XSAKMITKD8B8GPHGLQY424SHKI8OKQXXQN8BG435OKAMLFEN"  
+  input_ids = tokenizer.encode(prompt, return_tensors="pt").to(device)  
+  # Generate text with a maximum length of 4096 tokens
+  max_length = 4096
+  output = model.generate(input_ids, max_length=max_length)
+  # Move the output tensor back to CPU and decode the generated output
+  # Decode the generated output
+  generated_fhir = tokenizer.decode(output[0], skip_special_tokens=True)
+  print("Generated Summary:", generated_fhir)
+```
+The outputted Gneerated FHIR will look like this:
+```
+[resourceType] Procedure [id] efffddd8-effa-effa-ffaa-ffaffffffff [meta][profile][0] http://hl7.org/fhir/us/core/StructureDefinition/us-core-procedure [status] completed [code][coding][0][system] http://snomed.info/sct [code][coding][0][code] 430193006 [code][coding][0][display] Medication Reconciliation (procedure) [code][text] Medication Reconciliation (procedure) [subject][reference] Patient/fffffffd-fffa-fffa-fffa-fffffffffff [encounter][reference] Encounter/ffffffff-fffa-fffa-fffa-fffffffffff [performedPeriod][start] 2020-03-09T11:38:21-05:00 [performedPeriod][end] 2020-03-09T11:36:21-05:00 [location][reference] Location?identifier=https://github.com/synthetichealth/synthea|fffd0bf3-ffaa-3efd-affa-fffdfffffff [location][display] afffd0d-faed-bffa-fffa-fffffffffff [location][display] PCP237a3-faed-ffaa-ffffffffff [location][reference] Location?identifier=https://github.com/synthea|fff0bff9-ffaa-dfdd-ffc5-ffffffffff [location][display] PCP23757
 ```
-
 ## Responsible AI Practices
 Transparency: This model card aims to provide a transparent view of the model's capabilities, limitations, and intended use-cases.