Model weights and tokenizer

config.json

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+{
+  "architectures": [
+    "RemBertForMaskedLM"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "bos_token_id": 1,
+  "classifier_dropout_prob": 0.1,
+  "eos_token_id": 2,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "input_embedding_size": 128,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-12,
+  "max_position_embeddings": 512,
+  "model_type": "rembert",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_embedding_size": 768,
+  "pad_token_id": 3,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float32",
+  "transformers_version": "4.16.2",
+  "type_vocab_size": 2,
+  "use_cache": true,
+  "vocab_size": 65536
+}

pytorch_model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:09b5fd7d00545c189013c8a40a3f9c63e122af203548b33fc15e6ff08abe07d8
+size 578460133

special_tokens_map.json

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+{}

tokenizer_config.json

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+{
+  "tokenizer_class": "PreTrainedTokenizerFast"
+}