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.gitattributes

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1_Pooling/config.json

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+{
+    "word_embedding_dimension": 768,
+    "pooling_mode_cls_token": false,
+    "pooling_mode_mean_tokens": true,
+    "pooling_mode_max_tokens": false,
+    "pooling_mode_mean_sqrt_len_tokens": false,
+    "pooling_mode_weightedmean_tokens": false,
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+    "include_prompt": true
+}

README.md

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+# SetFit E5 Base Category Classifier v1
+
+A SetFit model trained on E5-base for category classification.
+
+## Model Details
+- Base Model: E5-base
+- Task: Category classification
+
+## Usage
+[Add usage instructions]

config.json

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+{
+  "architectures": [
+    "XLMRobertaModel"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.55.2",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

config_sentence_transformers.json

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+{
+  "model_type": "SentenceTransformer",
+  "__version__": {
+    "sentence_transformers": "5.1.0",
+    "transformers": "4.55.2",
+    "pytorch": "2.7.1+cu118"
+  },
+  "prompts": {
+    "query": "",
+    "document": ""
+  },
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+  "similarity_fn_name": "cosine"
+}

config_setfit.json

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+{
+  "labels": [
+    "Business",
+    "Sports",
+    "Politics",
+    "Lifestyle",
+    "General News",
+    "Entertainment",
+    "Crime",
+    "Technology",
+    "Health",
+    "Science",
+    "Religion",
+    "Education"
+  ],
+  "normalize_embeddings": false
+}

model.safetensors

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model_head.pkl

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modules.json

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sentence_bert_config.json

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+    "do_lower_case": false
+}

special_tokens_map.json

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tokenizer_config.json

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