commit files to HF hub

README.md

@@ -28,14 +28,14 @@ pip install --upgrade huggingface_hub
 from huggingface_hub import hf_hub_download
 import sys
 # Download the custom model code
-bert_gts_pretrained = hf_hub_download(repo_id="gauneg/bert-gts-absa-triple", filename="bert_gts_pretrained.py")
+bert_gts_pretrained = hf_hub_download(repo_id="gauneg/bert-gts-absa-triple", filename="bert_opinion.py")
 post =  hf_hub_download(repo_id="gauneg/bert-gts-absa-triple", filename="post.py")
 
 sys.path.append(bert_gts_pretrained.rsplit("/", 1)[0])
 sys.path.append(post.rsplit("/", 1)[0])
 
 
-from bert_gts_pretrained import GTSBertBaseABSATriple
+from bert_gts_pretrained import BertGTSOpinionTriple
 from post import DecodeAndEvaluate
 
 
@@ -44,7 +44,7 @@ from transformers import AutoTokenizer
 
 model_id = 'gauneg/bert-gts-absa-triple'
 tokenizer = AutoTokenizer.from_pretrained(model_id)
-model = GTSBertBaseABSATriple.from_pretrained(model_id)
+model = BertGTSOpinionTriple.from_pretrained(model_id)
 dec_and_infer = DecodeAndEvaluate(tokenizer)
 test_sentence0 = """I charge it at night and skip taking the cord with me because of the good battery life ."""
 test_sentence = "The Dell Inspiron 14 Plus is the most well-rounded laptop with great display and battery life that money can buy."

bert_gts_pretrained.py → bert_opinion.py

@@ -3,22 +3,23 @@ from transformers import AutoTokenizer, AutoModel, PreTrainedModel, PretrainedCo
 import torch.nn.functional as F
 
 
-class GTSBertBaseABSATripleConfig(PretrainedConfig):
-    def __init__(self, feat_dim = 768, max_len=64, class_num=6, **kwargs):
+class BertGTSOpinionTripleConfig(PretrainedConfig):
+    model_type = 'multi-infer-bert-uncased' 
+    def __init__(self, feat_dim = 768, max_len=128, class_num=6, **kwargs):
         super().__init__(**kwargs)
         self.feat_dim = feat_dim
         self.max_len = max_len
         self.class_num = class_num
 
-class GTSBertBaseABSATriple(PreTrainedModel):
-    config_class = GTSBertBaseABSATripleConfig
+class BertGTSOpinionTriple(PreTrainedModel):
+    config_class = BertGTSOpinionTripleConfig
     def __init__(self, config):
         model_id = 'google-bert/bert-base-uncased'
         super().__init__(config)
         self.model = AutoModel.from_pretrained(model_id)     
         self.max_seq_len = config.max_len
-        self.bert_feat_dim = config.feat_dim#768
-        self.class_num = config.class_num#6
+        self.bert_feat_dim = config.feat_dim #768
+        self.class_num = config.class_num #6
         self.cls_linear = torch.nn.Linear(self.bert_feat_dim*2, self.class_num)
         self.feature_linear = torch.nn.Linear(self.bert_feat_dim*2+self.class_num*3, self.bert_feat_dim*2)
         self.dropout_output = torch.nn.Dropout(0.1)

config.json

@@ -1,11 +1,11 @@
 {
   "architectures": [
-    "MultiInferBertUncased"
+    "BertGTSOpinionTriple"
   ],
   "class_num": 6,
   "feat_dim": 768,
-  "max_len": 64,
-  "model_type": "gts_opinion_triple",
+  "max_len": 128,
+  "model_type": "multi-infer-bert-uncased",
   "torch_dtype": "float32",
-  "transformers_version": "4.42.3"
+  "transformers_version": "4.44.2"
 }

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:cf4d4d02fb6b5d28e9c8008034866fad48cc684579d46c14b8521bdc0e98b736
+oid sha256:07a9f26340c6df71c594416b6dc5813a919cef064c1f540fd0c87377e53fec7e
 size 447543680