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updated read me

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  1. .gitattributes +6 -0
  2. README.md +3 -3
.gitattributes CHANGED
@@ -20,3 +20,9 @@ t5-small-wav2vec2-grammar-fixer/tokenizer_config.json filter=lfs diff=lfs merge=
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  t5-small-wav2vec2-grammar-fixer/config.json filter=lfs diff=lfs merge=lfs -text
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  t5-small-wav2vec2-grammar-fixer/pytorch_model.bin filter=lfs diff=lfs merge=lfs -text
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  t5-small-wav2vec2-grammar-fixer/special_tokens_map.json filter=lfs diff=lfs merge=lfs -text
 
 
 
 
 
 
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  t5-small-wav2vec2-grammar-fixer/config.json filter=lfs diff=lfs merge=lfs -text
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  t5-small-wav2vec2-grammar-fixer/pytorch_model.bin filter=lfs diff=lfs merge=lfs -text
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  t5-small-wav2vec2-grammar-fixer/special_tokens_map.json filter=lfs diff=lfs merge=lfs -text
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+ config.json filter=lfs diff=lfs merge=lfs -text
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+ pytorch_model.bin filter=lfs diff=lfs merge=lfs -text
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+ special_tokens_map.json filter=lfs diff=lfs merge=lfs -text
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+ spiece.model filter=lfs diff=lfs merge=lfs -text
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+ tf_model.h5 filter=lfs diff=lfs merge=lfs -text
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+ tokenizer_config.json filter=lfs diff=lfs merge=lfs -text
README.md CHANGED
@@ -34,11 +34,11 @@ print(f"{sentence}")
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  INPUT 1:
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  ```
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- BEFORE HE HAD TIME TO ANSWER A MUCH ENCUMBERED VERA BURST INTO THE ROOM WITH THE QUESTION I SAY CAN I LEAVE THESE HERE IN TWO THOUSAND AND TWO THESE WERE A SMALL BLACK PIG AND A LUSTY SPECIMEN OF BLACK RED GAME COCK
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  ```
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  OUTPUT 1:
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  ```
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- Before he had time to answer a much encumbered vara burst into the room with the question, I say, can I leave these here. In 2002, these were a small black pig and a lusty specimen of black red game cock.
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  ```
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  INPUT 2:
@@ -48,7 +48,7 @@ GOING ALONG SLUSHY COUNTRY ROADS AND SPEAKING TO DAMP AUDIENCES IN DRAUGHTY SCHO
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  OUTPUT 2:
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  ```
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- Going along Slushy Country Roads and speaking to damp audiences in Draughty School Rooms Day After day for a weekend, he'll have to put in an appearance at some place of worship on Sunday morning and he can come to us immediately afterwards.
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  ```
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  I strongly recommend improving the performance via further fine-tuning or by training more examples.
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  - Possible Quick Rule based improvements: Align the transcribed version and the generated version. If the similarity of two words (case-insensitive) vary by more than some threshold based on some similarity metric (e.g. Levenshtein), then keep the transcribed word.
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  INPUT 1:
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  ```
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+ WHEN ARE YOU COMING TOMORROW I AM ASKING BECAUSE OF THE MONEY YOU OWE ME PLEASE GIVE IT TO ME I AM WAITING YOU HAVE BEEN AVOIDING ME SINCE TWO THOUSAND AND THREE
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  ```
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  OUTPUT 1:
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  ```
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+ When are you coming tomorrow? I am asking because of the money you owe me, please give it to me. I am waiting. You have been avoiding me since 2003.
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  ```
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  INPUT 2:
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  OUTPUT 2:
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  ```
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+ Going along Slushy Country Roads and speaking to Damp audiences in Draughty School rooms day after day for a fortnight, he'll have to put in an appearance at some place of worship on Sunday morning and he can come to us immediately afterwards.
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  ```
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  I strongly recommend improving the performance via further fine-tuning or by training more examples.
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  - Possible Quick Rule based improvements: Align the transcribed version and the generated version. If the similarity of two words (case-insensitive) vary by more than some threshold based on some similarity metric (e.g. Levenshtein), then keep the transcribed word.