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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. |
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If this interests you, check out https://huggingface.co/BigSalmon/MrLincoln12 or my other MrLincoln repos. |
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``` |
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from transformers import AutoTokenizer, AutoModelWithLMHead |
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tokenizer = AutoTokenizer.from_pretrained("gpt2") |
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model = AutoModelWithLMHead.from_pretrained("BigSalmon/ParaphraseParentheses2.0") |
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``` |
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Example Prompt: |
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``` |
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the nba is [mask] [mask] viewership. |
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the nba is ( facing / witnessing / confronted with / suffering from / grappling with ) ( lost / tanking ) viewership... |
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ai is certain to [mask] the third industrial revolution. |
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ai is certain to ( breed / catalyze / inaugurate / catalyze / usher in / call forth / turn loose / lend its name to ) the third industrial revolution. |
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the modern-day knicks are a disgrace to [mask]. |
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the modern-day knicks are a disgrace to the franchise's ( rich legacy / tradition of excellence / uniquely distinguished record ). |
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HuggingFace is [mask]. |
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HuggingFace is ( an amazing company / |
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``` |
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``` |
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import torch |
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prompt = "Insert Your Prompt Here. It is Best To Have a Few Examples Before Like The Example Prompt Shows." |
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text = tokenizer.encode(prompt) |
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myinput, past_key_values = torch.tensor([text]), None |
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myinput = myinput |
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myinput= myinput.to(device) |
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logits, past_key_values = model(myinput, past_key_values = past_key_values, return_dict=False) |
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logits = logits[0,-1] |
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probabilities = torch.nn.functional.softmax(logits) |
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best_logits, best_indices = logits.topk(500) |
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best_words = [tokenizer.decode([idx.item()]) for idx in best_indices] |
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text.append(best_indices[0].item()) |
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best_probabilities = probabilities[best_indices].tolist() |
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words = [] |
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for i in range(500): |
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m = ([best_words[i]]) |
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m = str(m) |
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m = m.replace("[' ", "").replace("']", "") |
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print(m) |
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``` |