Create README.md

README.md

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+This can be used to paraphrase. I recommend using the code I have attached below. You can generate it without using LogProbs, but you are likely to be best served by manually examining the most likely outputs.
+
+```
+from transformers import AutoTokenizer, AutoModelWithLMHead
+tokenizer = AutoTokenizer.from_pretrained("gpt2")
+model = AutoModelWithLMHead.from_pretrained("BigSalmon/ParaphraseParentheses2.0")
+```
+
+Example Prompt:
+```
+the nba is [mask] [mask] viewership.
+the nba is ( facing / witnessing / confronted with / suffering from / grappling with ) ( lost / tanking ) viewership...
+
+ai is certain to [mask] the third industrial revolution.
+ai is certain to ( breed / catalyze / inaugurate / catalyze / usher in / call forth / turn loose / lend its name to ) the third industrial revolution.
+
+the modern-day knicks are a disgrace to [mask].
+the modern-day knicks are a disgrace to the franchise's ( rich legacy / tradition of excellence / uniquely distinguished record ).
+
+HuggingFace is [mask].
+HuggingFace is ( an amazing company /
+```
+
+```
+import torch
+prompt = "Insert Your Prompt Here. It is Best To Have a Few Examples Before Like The Example Prompt Shows."
+text = tokenizer.encode(prompt)
+myinput, past_key_values = torch.tensor([text]), None
+myinput = myinput
+myinput= myinput.to(device)
+logits, past_key_values = model(myinput, past_key_values = past_key_values, return_dict=False)
+logits = logits[0,-1]
+probabilities = torch.nn.functional.softmax(logits)
+best_logits, best_indices = logits.topk(500)
+best_words = [tokenizer.decode([idx.item()]) for idx in best_indices]
+text.append(best_indices[0].item())
+best_probabilities = probabilities[best_indices].tolist()
+words = []
+for i in range(500):
+    m = ([best_words[i]])
+    m = str(m)
+    m = m.replace("[' ", "").replace("']", "")
+    print(m)
+```