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--- |
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license: mit |
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language: |
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- it |
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--- |
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This model is a fine-tuned version of [bart-it](https://huggingface.co/morenolq/bart-it) on a lfqa dataset (pubmed_qa, webgpt_comparisons, sapere.it, stackexchange_titlebody_best_voted_answer_jsonl, lfqa_preprocessed - partially translated) |
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### Usage |
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```python |
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import torch |
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from transformers import AutoTokenizer, AutoModelForSeq2SeqLM |
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model_name = "efederici/bart-lfqa-it" |
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device = torch.device('cuda' if torch.cuda.is_available() else 'cpu') |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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model = AutoModelForSeq2SeqLM.from_pretrained(model_name) |
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model = model.to(device) |
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query = "<string>" |
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documents = [ |
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"<string>", |
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"<string>", |
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... |
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] |
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docs = "<p> " + " <p> ".join([d for d in documents]) |
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q = "Q: {}\n\nC: {}".format(query, docs) |
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input_qc = tokenizer(query_and_docs, truncation=True, padding=True, return_tensors="pt") |
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generated_answers_encoded = model.generate( |
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input_ids=input_qc["input_ids"].to(device), |
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attention_mask=input_qc["attention_mask"].to(device), |
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min_length=64, |
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max_length=256, |
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do_sample=False, |
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early_stopping=True, |
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num_beams=8, |
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temperature=1.0, |
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top_k=None, |
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top_p=None, |
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eos_token_id=tokenizer.eos_token_id, |
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no_repeat_ngram_size=3, |
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num_return_sequences=1 |
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) |
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output = tokenizer.batch_decode(generated_answers_encoded, skip_special_tokens=True,clean_up_tokenization_spaces=True)[0] |
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print(output) |
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``` |
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### Author |
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- Edoardo Federici: [Twitter](https://twitter.com/edofederici) | [LinkedIn](https://www.linkedin.com/in/edoardo-federici-01341b1b6) |
