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README.md ADDED
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+ # Query Generation
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+ This model is the t5-base model from [docTTTTTquery](https://github.com/castorini/docTTTTTquery).
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+
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+ The T5-base model was trained on the [MS MARCO Passage Dataset](https://github.com/microsoft/MSMARCO-Passage-Ranking), which consists of about 500k real search queries from Bing together with the relevant passage.
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+
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+ The model can be used for query generation to learn semantic search models without requiring annotated training data: [Synthetic Query Generation](https://github.com/UKPLab/sentence-transformers/tree/master/examples/unsupervised_learning/query_generation).
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+
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+
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+ ## Usage
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+
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+ ```python
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+ from transformers import T5Tokenizer, T5ForConditionalGeneration
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+
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+ tokenizer = T5Tokenizer.from_pretrained('model-name')
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+ model = T5ForConditionalGeneration.from_pretrained('model-name')
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+
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+ para = "Python is an interpreted, high-level and general-purpose programming language. Python's design philosophy emphasizes code readability with its notable use of significant whitespace. Its language constructs and object-oriented approach aim to help programmers write clear, logical code for small and large-scale projects."
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+
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+ input_ids = tokenizer.encode(para, return_tensors='pt')
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+ outputs = model.generate(
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+ input_ids=input_ids,
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+ max_length=64,
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+ do_sample=True,
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+ top_p=0.95,
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+ num_return_sequences=3)
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+
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+ print("Paragraph:")
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+ print(para)
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+
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+ print("\nGenerated Queries:")
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+ for i in range(len(outputs)):
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+ query = tokenizer.decode(outputs[i], skip_special_tokens=True)
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+ print(f'{i + 1}: {query}')
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+ ```
config.json ADDED
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+ {
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+ "_name_or_path": "model_raw/t5-large/model.ckpt-1004700",
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+ "architectures": [
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+ "T5ForConditionalGeneration"
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+ ],
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+ "d_ff": 4096,
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+ "d_kv": 64,
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+ "d_model": 1024,
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+ "decoder_start_token_id": 0,
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+ "dropout_rate": 0.1,
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+ "eos_token_id": 1,
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+ "feed_forward_proj": "relu",
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+ "initializer_factor": 1.0,
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+ "is_encoder_decoder": true,
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+ "layer_norm_epsilon": 1e-06,
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+ "model_type": "t5",
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+ "n_positions": 512,
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+ "num_decoder_layers": 24,
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+ "num_heads": 16,
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+ "num_layers": 24,
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+ "output_past": true,
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+ "pad_token_id": 0,
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+ "relative_attention_num_buckets": 32,
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+ "task_specific_params": {
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+ "summarization": {
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+ "early_stopping": true,
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+ "length_penalty": 2.0,
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+ "max_length": 200,
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+ "min_length": 30,
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+ "no_repeat_ngram_size": 3,
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+ "num_beams": 4,
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+ "prefix": "summarize: "
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+ },
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+ "translation_en_to_de": {
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+ "early_stopping": true,
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+ "max_length": 300,
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+ "num_beams": 4,
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+ "prefix": "translate English to German: "
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+ },
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+ "translation_en_to_fr": {
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+ "early_stopping": true,
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+ "max_length": 300,
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+ "num_beams": 4,
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+ "prefix": "translate English to French: "
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+ },
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+ "translation_en_to_ro": {
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+ "early_stopping": true,
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+ "max_length": 300,
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+ "num_beams": 4,
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+ "prefix": "translate English to Romanian: "
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+ }
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+ },
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+ "transformers_version": "4.2.2",
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+ "use_cache": true,
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+ "vocab_size": 32128
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+ }
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special_tokens_map.json ADDED
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tokenizer_config.json ADDED
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