oluwatosin adewumi commited on
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bc3a45b
1 Parent(s): 60a5b1e

code fixed

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  1. README.md +2 -2
README.md CHANGED
@@ -24,7 +24,7 @@ More information about the original pre-trained model can be found [here](https:
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  * Classification examples:
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  |Prediction | Input |
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  |---------|------------|
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- |0 | "selective kindness : in europe , some refugees are more equal than others" |
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  |1 | he said their efforts should not stop only at creating many graduates but also extended to students from poor families so that they could break away from the cycle of poverty |
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  ### How to use
@@ -32,8 +32,8 @@ More information about the original pre-trained model can be found [here](https:
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  ```python
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  from transformers import T5ForConditionalGeneration, T5Tokenizer
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  import torch
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- tokenizer = T5Tokenizer.from_pretrained("tosin/pcl_22")
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  model = T5ForConditionalGeneration.from_pretrained("tosin/pcl_22")
 
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  tokenizer.pad_token = tokenizer.eos_token
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  input_ids = tokenizer("he said their efforts should not stop only at creating many graduates but also extended to students from poor families so that they could break away from the cycle of poverty", padding=True, truncation=True, return_tensors='pt').input_ids
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  outputs = model.generate(input_ids)
 
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  * Classification examples:
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  |Prediction | Input |
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  |---------|------------|
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+ |0 | selective kindness : in europe , some refugees are more equal than others |
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  |1 | he said their efforts should not stop only at creating many graduates but also extended to students from poor families so that they could break away from the cycle of poverty |
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  ### How to use
 
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  ```python
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  from transformers import T5ForConditionalGeneration, T5Tokenizer
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  import torch
 
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  model = T5ForConditionalGeneration.from_pretrained("tosin/pcl_22")
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+ tokenizer = T5Tokenizer.from_pretrained("t5-base") # use the source tokenizer because T5 finetuned tokenizer breaks
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  tokenizer.pad_token = tokenizer.eos_token
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  input_ids = tokenizer("he said their efforts should not stop only at creating many graduates but also extended to students from poor families so that they could break away from the cycle of poverty", padding=True, truncation=True, return_tensors='pt').input_ids
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  outputs = model.generate(input_ids)