| # T5-base data to text model specialized for Finance NLG | |
| __simple version__ | |
| This model was trained on a limited number of indicators, values and dates | |
| ---- | |
| ## Usage (HuggingFace Transformers) | |
| #### Call the model | |
| ```python | |
| from transformers import AutoTokenizer, AutoModelForSeq2SeqLM | |
| tokenizer = AutoTokenizer.from_pretrained("yseop/FNP_T5_D2T_simple") | |
| model = AutoModelForSeq2SeqLM.from_pretrained("yseop/FNP_T5_D2T_simple") | |
| text = ["Group profit | valIs | $ 10 && € $10 | 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])) | |
| ``` | |
| **Created by:** [Yseop](https://www.yseop.com/) | Pioneer in Natural Language Generation (NLG) technology. Scaling human expertise through Natural Language Generation. |