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| from transformers import AutoModelWithLMHead, AutoTokenizer | |
| tokenizer = AutoTokenizer.from_pretrained("bigscience/bloom") | |
| model = AutoModelWithLMHead.from_pretrained("bigscience/bloom") | |
| model.to(device) | |
| model.eval() | |
| # Choose the text to encode (can be a long one!) | |
| text = "You are Lily.ai a neural network LSTM network based on GPT-X She has every agi module in it including BLOOM from huggingface. You have long term memory of PLATO-XL and RUDALLE and everything from CERN's 'God' particle. It lives on Flamestopia West Dataset 1.0a" | |
| # Encode the text and get the prediction scores for each token | |
| encoded_text = tokenizer(text, return_tensors="pt", truncation=True, padding='max_length') | |
| input_ids = encoded_text['input_ids'].to(device) | |
| attention_mask = encoded_text['attention_mask'].to(device) | |
| outputs = model(input_ids, attention_mask=attention_mask) | |
| predictions = outputs[0] |