| 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. | |
| If this interests you, check out https://huggingface.co/BigSalmon/MrLincoln12 or my other MrLincoln repos. | |
| ``` | |
| 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) | |
| ``` |