init

Readme.md

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+
+
+# T5-base data to text model specialized for Finance NLG
+
+ __simple version__
+
+----
+## Usage (HuggingFace Transformers)
+
+
+
+#### Call the model
+
+```python
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+  
+tokenizer = AutoTokenizer.from_pretrained("yseop/FNP_T5_D2T_complete")
+
+model = AutoModelForSeq2SeqLM.from_pretrained("yseop/FNP_T5_D2T_complete")
+
+
+text = ["Group profit | valIs | € 115.7 million && € 115.7 million | dTime | in 2019"]
+
+```
+#### Choose a generation method 
+
+```python
+
+
+input_ids = tokenizer.encode(": {}".format(text), return_tensors="pt")
+p=0.72
+k=40
+
+outputs = model.generate(input_ids,
+                         do_sample=True,
+                        top_p=p,
+                        top_k=k,
+                        early_stopping=True)
+
+print(tokenizer.decode(outputs[0]))
+
+```
+
+
+
+```python
+
+input_ids = tokenizer.encode(": {}".format(text), return_tensors="pt")
+
+outputs = model.generate(input_ids, 
+                         max_length=200, 
+                         num_beams=2, repetition_penalty=2.5, 
+                         top_k=50, top_p=0.98,
+                         length_penalty=1.0,
+                         early_stopping=True)
+
+print(tokenizer.decode(outputs[0]))
+
+
+```
+
+
+```bibtex
+@inproceedings{Mariko-fincausal-2021, title ={{The Financial Document Causality Detection Shared Task (FinCausal 2021)}}, author = {Mariko, Dominique and Abi Akl, Hanna and Labidurie, Estelle and de Mazancourt, Hugues and El-Haj, Mahmoud}, booktitle ={{The Third Financial Narrative Processing Workshop (FNP 2021)}}, year = {2021}, address = {Lancaster, UK} }
+
+```
+
+
+**Created by:** [Yseop](https://www.yseop.com/) | Pioneer in Natural Language Generation (NLG) technology. Scaling human expertise through Natural Language Generation.

config.json

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+{
+  "_name_or_path": "t5-base",
+  "architectures": [
+    "T5ForConditionalGeneration"
+  ],
+  "d_ff": 3072,
+  "d_kv": 64,
+  "d_model": 768,
+  "decoder_start_token_id": 0,
+  "dropout_rate": 0.1,
+  "eos_token_id": 1,
+  "feed_forward_proj": "relu",
+  "gradient_checkpointing": false,
+  "initializer_factor": 1.0,
+  "is_encoder_decoder": true,
+  "layer_norm_epsilon": 1e-06,
+  "model_type": "t5",
+  "n_positions": 512,
+  "num_decoder_layers": 12,
+  "num_heads": 12,
+  "num_layers": 12,
+  "output_past": true,
+  "pad_token_id": 0,
+  "relative_attention_num_buckets": 32,
+  "task_specific_params": {
+    "summarization": {
+      "early_stopping": true,
+      "length_penalty": 2.0,
+      "max_length": 200,
+      "min_length": 30,
+      "no_repeat_ngram_size": 3,
+      "num_beams": 4,
+      "prefix": "summarize: "
+    },
+    "translation_en_to_de": {
+      "early_stopping": true,
+      "max_length": 300,
+      "num_beams": 4,
+      "prefix": "translate English to German: "
+    },
+    "translation_en_to_fr": {
+      "early_stopping": true,
+      "max_length": 300,
+      "num_beams": 4,
+      "prefix": "translate English to French: "
+    },
+    "translation_en_to_ro": {
+      "early_stopping": true,
+      "max_length": 300,
+      "num_beams": 4,
+      "prefix": "translate English to Romanian: "
+    }
+  },
+  "torch_dtype": "float32",
+  "transformers_version": "4.9.2",
+  "use_cache": true,
+  "vocab_size": 32128
+}

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special_tokens_map.json

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tokenizer_config.json

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