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import gradio as gr |
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM |
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tokenizer = AutoTokenizer.from_pretrained("impresso-project/nel-hipe-multilingual") |
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model = AutoModelForSeq2SeqLM.from_pretrained( |
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"impresso-project/nel-hipe-multilingual" |
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).eval() |
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print("Model loaded successfully!") |
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def disambiguate_sentence(sentence): |
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results = [] |
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for sentence in [sentence]: |
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outputs = model.generate( |
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**tokenizer([sentence], return_tensors="pt"), |
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num_beams=5, |
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num_return_sequences=5 |
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) |
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decoded = tokenizer.batch_decode(outputs, skip_special_tokens=True) |
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results.append(decoded) |
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return results |
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def nel_app_interface(): |
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input_sentence = gr.Textbox( |
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lines=5, |
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label="Input Sentence", |
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placeholder="Enter your sentence here in the following format: // << We are going to [START] Paris [END]. >>" |
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" // This format ensures that the model knows which entities to disambiguate, more exactly the " |
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"entity should be surrounded by `[START]` and `[END]`. // " |
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"!Only one entity per sentence is supported at the moment!", |
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) |
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output_entities = gr.HighlightedText(label="Extracted Entities") |
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interface = gr.Interface( |
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fn=disambiguate_sentence, |
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inputs=input_sentence, |
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outputs=output_entities, |
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title="Entity Linking with impresso-project/nel-hipe-multilingual", |
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description="Link entities using the `impresso-project/nel-hipe-multilingual` model under the hood!", |
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examples=[ |
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[ |
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"Des chercheurs de l' [START] Université de Cambridge [END] ont développé une nouvelle technique de calcul " |
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"quantique qui promet d'augmenter exponentiellement les vitesses de calcul.", |
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"Le rapport complet sur ces découvertes a été publié dans la prestigieuse revue 'Nature Physics'. ([START] " |
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"Reuters [END])", |
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"In the [START] year 1789 [END], the Estates-General was convened in France.", |
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"[START] King Louis XVI, ruler of France [END], called for the meeting.", |
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"The event was held at the [START] Palace of Versailles [END], a symbol of French monarchy.", |
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"At Versailles, Marie Antoinette, the Queen of France, was involved in discussions.", |
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"Maximilien Robespierre, a leading member of the National Assembly, also participated.", |
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"[START] Jean-Jacques Rousseau, the famous philosopher [END], was a significant figure in the debate.", |
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"Another important participant was [START] Charles de Talleyrand, the Bishop of Autun [END].", |
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"Meanwhile, across the Atlantic, [START] George Washington, the first President of the United States [END], " |
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"was shaping policies.", |
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"[START] Thomas Jefferson, the nation's Secretary of State [END], played a key role in drafting policies for " |
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"the new American government.", |
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] |
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], |
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) |
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interface.launch() |
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if __name__ == "__main__": |
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nel_app_interface() |
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