jpcorb20 commited on
Commit
7977371
1 Parent(s): cb8bf60

Update README.md

Browse files
Files changed (1) hide show
  1. README.md +22 -1
README.md CHANGED
@@ -43,4 +43,25 @@ Used the _example/seq2seq/run_summarization.py_ script from the transformers sou
43
  eval_rouge2: 23.6137,\
44
  eval_rougeL: 37.2397,\
45
  eval_rougeLsum: 42.7126,\
46
- eval_samples_per_second: 4.302
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
43
  eval_rouge2: 23.6137,\
44
  eval_rougeL: 37.2397,\
45
  eval_rougeLsum: 42.7126,\
46
+ eval_samples_per_second: 4.302
47
+
48
+ ## Example
49
+
50
+ from transformers import PegasusForConditionalGeneration, PegasusTokenizer
51
+
52
+ model_name = "jpcorb20/pegasus-large-reddit_tifu-samsum-256"
53
+
54
+ tokenizer = PegasusTokenizer.from_pretrained(model_name)
55
+ model = PegasusForConditionalGeneration.from_pretrained(model_name)
56
+
57
+ src_text = """Carter: Hey Alexis, I just wanted to let you know that I had a really nice time with you tonight.\r\nAlexis: Thanks Carter. Yeah, I really enjoyed myself as well.\r\nCarter: If you are up for it, I would really like to see you again soon.\r\nAlexis: Thanks Carter, I'm flattered. But I have a really busy week coming up.\r\nCarter: Yeah, no worries. I totally understand. But if you ever want to go grab dinner again, just let me know.\r\nAlexis: Yeah of course. Thanks again for tonight. Carter: Sure. Have a great night.\r\n"""
58
+
59
+ token_params = dict(max_length=256, truncation=True, padding='longest', return_tensors="pt")
60
+ batch = tokenizer(src_text, **token_params)
61
+
62
+ translated = model.generate(**batch)
63
+
64
+ decode_params = dict(num_beams=5, min_length=16, max_length=128, length_penalty=2)
65
+ tgt_text = tokenizer.batch_decode(translated, skip_special_tokens=True, **decode_params)
66
+
67
+ print(tgt_text)