ShishuTripathi commited on
Commit
b5568be
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1 Parent(s): a9a8be4

Update app.py

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  1. app.py +17 -13
app.py CHANGED
@@ -1,24 +1,28 @@
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- from transformers import AutoTokenizer, AutoModelForCausalLM
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  import torch
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  import gradio as gr
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- tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-neo-1.3B")
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- model = AutoModelForCausalLM.from_pretrained("EleutherAI/gpt-neo-1.3B")
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- def text_generation(input_text, seed):
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- input_ids = tokenizer(input_text, return_tensors="pt").input_ids
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- torch.manual_seed(seed) # Max value: 18446744073709551615
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- outputs = model.generate(input_ids, do_sample=True, min_length=50, max_length=200)
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- generated_text = tokenizer.batch_decode(outputs, skip_special_tokens=True)
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- return generated_text
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- title = "Text Generator Demo GPT-Neo"
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- description = "Text Generator Application by ecarbo"
 
 
 
 
 
 
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  gr.Interface(
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  text_generation,
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- [gr.inputs.Textbox(lines=2, label="Enter input text"), gr.inputs.Number(default=10, label="Enter seed number")],
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- [gr.outputs.Textbox(type="auto", label="Text Generated")],
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  title=title,
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  description=description,
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  theme="huggingface"
 
 
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  import torch
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  import gradio as gr
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+ from peft import PeftModel, PeftConfig
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+ from transformers import AutoModelForCausalLM, AutoTokenizer ,pipeline
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+ config = PeftConfig.from_pretrained("ShishuTripathi/entity_coder")
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+ model = AutoModelForCausalLM.from_pretrained("ybelkada/falcon-7b-sharded-bf16")
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+ model = PeftModel.from_pretrained(model, "ShishuTripathi/entity_coder")
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+ tokenizer = AutoTokenizer.from_pretrained("ShishuTripathi/entity_coder")
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+ generator = pipeline('text-generation' , model = model, tokenizer =tokenizer, max_length = 50)
 
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+ def text_generation(input_text):
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+ prompt = f"### Narrative: {input_text} \n ### Reported Term:"
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+ out = generator(prompt)
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+ output = out[0]['generated_text'].replace('|endoftext|',' ').strip()
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+ return output
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+
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+ title = "Preferred Term Extractor and Coder"
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+ description = "The term used to describe an adverse event in the Database of Adverse Event Notifications - medicines is the MedDRA 'preferred term', which describes a single medical concept"
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  gr.Interface(
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  text_generation,
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+ [gr.inputs.Textbox(lines=2, label="Enter Narrative or Phrase")],
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+ [gr.outputs.Textbox(type="auto", label="Extracted Preffered Term")],
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  title=title,
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  description=description,
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  theme="huggingface"