yeliu918 commited on
Commit
df6c59b
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1 Parent(s): c889fa8

update pooling for ST

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Files changed (3) hide show
  1. .DS_Store +0 -0
  2. 1_Pooling/config.json +10 -0
  3. README.md +2 -2
.DS_Store ADDED
Binary file (6.15 kB). View file
 
1_Pooling/config.json ADDED
@@ -0,0 +1,10 @@
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "word_embedding_dimension": 1024,
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+ "pooling_mode_cls_token": true,
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+ "pooling_mode_mean_tokens": false,
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+ "pooling_mode_max_tokens": false,
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+ "pooling_mode_mean_sqrt_len_tokens": false,
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+ "pooling_mode_weightedmean_tokens": false,
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+ "pooling_mode_lasttoken": false,
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+ "include_prompt": true
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+ }
README.md CHANGED
@@ -73,14 +73,14 @@ from sentence_transformers import SentenceTransformer
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  from sentence_transformers.util import cos_sim
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  sentences = [
 
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  "def quick_sort(arr):\n if len(arr) <= 1:\n return arr\n pivot = arr[len(arr) // 2]\n left = [x for x in arr if x < pivot]\n middle = [x for x in arr if x == pivot]\n right = [x for x in arr if x > pivot]\n return quick_sort(left) + middle + quick_sort(right)",
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  "def bubble_sort(arr):\n n = len(arr)\n for i in range(n):\n for j in range(0, n-i-1):\n if arr[j] > arr[j+1]:\n arr[j], arr[j+1] = arr[j+1], arr[j]\n return arr",
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- "how to implement quick sort in Python?"
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  ]
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  model = SentenceTransformer('Salesforce/SFR-Embedding-Code-400M_R', trust_remote_code=True)
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  embeddings = model.encode(sentences)
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- print(cos_sim(embeddings[0], embeddings[1]))
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  ```
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  ### Citation
 
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  from sentence_transformers.util import cos_sim
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  sentences = [
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+ "how to implement quick sort in Python?",
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  "def quick_sort(arr):\n if len(arr) <= 1:\n return arr\n pivot = arr[len(arr) // 2]\n left = [x for x in arr if x < pivot]\n middle = [x for x in arr if x == pivot]\n right = [x for x in arr if x > pivot]\n return quick_sort(left) + middle + quick_sort(right)",
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  "def bubble_sort(arr):\n n = len(arr)\n for i in range(n):\n for j in range(0, n-i-1):\n if arr[j] > arr[j+1]:\n arr[j], arr[j+1] = arr[j+1], arr[j]\n return arr",
 
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  ]
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  model = SentenceTransformer('Salesforce/SFR-Embedding-Code-400M_R', trust_remote_code=True)
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  embeddings = model.encode(sentences)
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+ print(cos_sim(embeddings[0], embeddings[1:]))
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  ```
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  ### Citation