fhirfly
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rapidfhir-procedures

Text2Text Generation

text-generation-inference

Inference Endpoints

Model card Files Files and versions Community

fhirfly commited on Sep 1, 2023

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cc48f2e

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1 Parent(s): 89dbadc

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@@ -43,8 +43,8 @@ Here's a simple Python code snippet to use this model:
 ```
   from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
-  tokenizer = AutoTokenizer.from_pretrained("rapidfhir-procedures")
-  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

 ```
   from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+  tokenizer = AutoTokenizer.from_pretrained("fhirfly/rapidfhir-procedures")
+  model = AutoModelForSeq2SeqLM.from_pretrained("fhirfly/rapidfhir-procedures")
   prompt = "SQM9PZ2545XHC4TE9RS27V183DD9KPW6JOI53UU5NYY8XRGIW6NZ0227WOAAW6NDNO79SR2K75T6J104XSAKMITKD8B8GPHGLQY424SHKI8OKQXXQN8BG435OKAMLFEN"
   input_ids = tokenizer.encode(prompt, return_tensors="pt").to(device)
   # Generate text with a maximum length of 4096 tokens