Create README.md

README.md

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