how much top to include

DOTS/feat.py

@@ -35,18 +35,18 @@
 
 
 # # Load models and tokenizers
-# model_name = "distilroberta-base"
-# model = AutoModel.from_pretrained(model_name)
-# tokenizer = AutoTokenizer.from_pretrained(model_name)
-# # !python -m spacy download en_core_web_sm
-# nlp = spacy.load('en_core_web_sm')
+model_name = "distilroberta-base"
+model = AutoModel.from_pretrained(model_name)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+# !python -m spacy download en_core_web_sm
+nlp = spacy.load('en_core_web_sm')
 
 # # Define constants
-# n_gram_range = (1, 2)
-# stop_words = "english"
-# embeddings=[]
-# device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
-# model.to(device)
+n_gram_range = (1, 2)
+stop_words = "english"
+embeddings=[]
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model.to(device)
 
 # Define functions
 def chunk_text(text, max_len):