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README.md

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+---
+datasets:
+- squad_v2
+language: en
+license: mit
+pipeline_tag: question-answering
+tags:
+- roberta
+- question-answering
+---
+# Roberta base model for QA (SQuAD 2.0)
+
+This model uses [roberta-base](https://huggingface.co/roberta-base).
+
+## Training Data
+The models have been trained on the [SQuAD 2.0](https://rajpurkar.github.io/SQuAD-explorer/) dataset.
+
+It can be used for question answering task.
+
+## Usage and Performance
+The trained model can be used like this:
+```python
+from transformers import AutoModelForQuestionAnswering, AutoTokenizer, pipeline
+
+# Load model & tokenizer
+roberta_model = AutoModelForQuestionAnswering.from_pretrained('navteca/roberta-base-squad2')
+roberta_tokenizer = AutoTokenizer.from_pretrained('navteca/roberta-base-squad2')
+
+# Get predictions
+nlp = pipeline('question-answering', model=roberta_model, tokenizer=roberta_tokenizer)
+
+result = nlp({
+    'question': 'How many people live in Berlin?',
+    'context': 'Berlin had a population of 3,520,031 registered inhabitants in an area of 891.82 square kilometers.'
+})
+
+print(result)
+
+#{
+#  "answer": "3,520,031"
+#  "end": 36,
+#  "score": 0.96186668,
+#  "start": 27,
+#}
+```

config.json

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+{
+  "architectures": [
+    "RobertaForQuestionAnswering"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "language": "english",
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "roberta",
+  "name": "Roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "pad_token_id": 1,
+  "position_embedding_type": "absolute",
+  "type_vocab_size": 1,
+  "vocab_size": 50265
+}

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special_tokens_map.json

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+{
+    "bos_token": {
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+        "single_word": false,
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+        "rstrip": false,
+        "normalized": true
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+}

tokenizer_config.json

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+{
+    "do_lower_case": false,
+    "full_tokenizer_file": null,
+    "model_max_length": 512,
+    "special_tokens_map_file": "special_tokens_map.json"
+}