20 lines
714 B
Python
20 lines
714 B
Python
from transformers import AutoTokenizer, AutoModel
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import torch
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# Load the tokenizer and the model
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tokenizer = AutoTokenizer.from_pretrained('allenai/scibert_scivocab_uncased')
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model = AutoModel.from_pretrained('allenai/scibert_scivocab_uncased')
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# Prepare a test input sentence (e.g., "Hello, world!")
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input_text = "Hello, world!"
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# Tokenize the input text and convert it to input IDs
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inputs = tokenizer(input_text, return_tensors="pt") # Return tensors in PyTorch format
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# Forward pass through the model
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with torch.no_grad(): # Disable gradient calculation since we are only doing inference
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outputs = model(**inputs)
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# Output model's hidden states (for the last layer)
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print(outputs.last_hidden_state)
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