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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ tags:
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+ - bert
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+ - kcbert
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+ - kor-hate-sentence
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+ - sentimental-analysis
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+ ---
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+
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+ # SJ-Donald/kor-hate-sentence
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+
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+ SJ-Donald/kor-hate-sentence is pretrained model using follow:
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+
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+ ## Models
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+
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+ * [beomi/kcbert-large](https://huggingface.co/beomi/kcbert-large)
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+
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+ ## Datasets
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+
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+ * [SJ-Donald/kor-hate-sentence](https://huggingface.co/datasets/SJ-Donald/kor-hate-sentence)
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+
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+ ## How to use
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+
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+ ```Python
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+ from transformers import TextClassificationPipeline, BertForSequenceClassification, AutoTokenizer+
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+
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+ model_name = 'SJ-Donald/kor-hate-sentence'
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+ model = BertForSequenceClassification.from_pretrained(model_name)
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+
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+ tokenizer = AutoTokenizer.from_pretrained(model_name)
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+
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+ pipe = TextClassificationPipeline(
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+ model = model,
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+ tokenizer = tokenizer,
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+ device = 0, # cpu: -1, gpu: gpu number
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+ return_all_scores = True,
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+ function_to_apply = 'sigmoid'
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+ )
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+
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+ for result in pipe("이딴 게임할 거면 방송 그만해라 어휴")[0]:
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+ print(result)
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+
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+ {'label': 'hate', 'score': 0.7051385641098022}
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+ {'label': 'clean', 'score': 0.29405009746551514}
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+ ```
config.json ADDED
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+ {
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+ "_name_or_path": "beomi/kcbert-base",
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+ "architectures": [
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+ "BertForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "classifier_dropout": null,
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+ "directionality": "bidi",
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "hate",
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+ "1": "clean"
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+ },
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "label2id": {
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+ "clean": 1,
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+ "hate": 0
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 300,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 0,
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+ "pooler_fc_size": 768,
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+ "pooler_num_attention_heads": 12,
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+ "pooler_num_fc_layers": 3,
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+ "pooler_size_per_head": 128,
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+ "pooler_type": "first_token_transform",
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+ "position_embedding_type": "absolute",
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+ "problem_type": "multi_label_classification",
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.35.2",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 30000
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+ }
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