Update README.md

README.md

@@ -1,10 +1,15 @@
 ## Overview
 This is a LoRA adapter for google/flan-ul2 available on huggingface. It takes as input a text document and outputs a synopsis and document classifier tags.
 
+You can use this to convert your training data into conditional pretraining examples.
+
 ```
 import torch
 from peft import PeftModel, PeftConfig
 from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+import math
+
+device_id=0
 
 # Load device map for FLAN_UL2
 device_map = {
@@ -45,7 +50,7 @@ def generate_condlabels(input_text):
         penalty_alpha=0.6,
         top_k=5,
         bos_token_id=0,
-        eos_token_id=2,
+        eos_token_id=1,
         repetition_penalty=1.0,
         return_dict_in_generate=True,
         output_scores=True,
@@ -88,5 +93,9 @@ We have developed a fine tuned LoRA model based on the open source FLAN-UL2 that
 """
 
 # Generate outputs for a list of strings
-generate_condlabels([text])
+output=generate_condlabels([text])
+print(output[0][0])
+
+"""<pad> Synopsis: The document outlines the conditional pretraining of large language models and provides information about the ChatGPT project. Tags: [ human language understanding, conditional pretraining, chatbots, machine learning]</s>"""
+
 ```