
<pre>
labels map = 
  {
  "0": "Gastroenterology",
  "1": "Neurology",
  "2": "Orthopedic",
  "3": "Radiology",
  "4": "Urology"
}
</pre>

<h2><i>The fine tuned model has been trained on around 2300 medical transcriptions, to classify medical specialty.
  More classes will be added as data would be available.</i></h2>
{"language": ["en"], "tags": ["ditilbert", "text classification", "clinical notes", "wellnation"]}
transformers tf distilbert text-classification ditilbert text classification clinical notes wellnation en autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #distilbert #text-classification #ditilbert #text classification #clinical notes #wellnation #en #autotrain_compatible #endpoints_compatible #region-us 


<pre>
labels map = 
  {
  "0": "Gastroenterology",
  "1": "Neurology",
  "2": "Orthopedic",
  "3": "Radiology",
  "4": "Urology"
}
</pre>

<h2><i>The fine tuned model has been trained on around 2300 medical transcriptions, to classify medical specialty.
  More classes will be added as data would be available.</i></h2>
TAGS
#transformers #tf #distilbert #text-classification #ditilbert #text classification #clinical notes #wellnation #en #autotrain_compatible #endpoints_compatible #region-us 
