Initial Query

How do I get all tokens in a AutoTokenizer?

LLM Generation

Query

How do I get all tokens in a AutoTokenizer?

Output

To get all tokens in an `AutoTokenizer` from the Hugging Face Transformers library, you can use the `tokenizer.vocab` or `tokenizer.get_vocab()` attribute. However, the most straightforward way is to use the `tokenizer.get_vocab()` method or access the `tokenizer.vocab` dictionary directly. Here is a simple example using the `AutoTokenizer`: 

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from transformers import AutoTokenizer

# Load a tokenizer
tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")

# Get all tokens
all_tokens = list(tokenizer.vocab.keys())

# Print all tokens
for token in all_tokens:
    print(token)
Alternatively, you can use the `tokenizer.get_vocab()` method which returns a dictionary where the keys are the tokens and the values are their respective IDs: 
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all_tokens_dict = tokenizer.get_vocab()
for token, token_id in all_tokens_dict.items():
    print(f"Token: {token}, ID: {token_id}")
Note that `tokenizer.vocab` is a dictionary that maps token strings to their IDs, and `tokenizer.get_vocab()` returns the same dictionary. Remember, the specific tokens available depend on the model you're using (e.g., BERT, RoBERTa, etc.), as different models may have slightly different tokenizations.

Substring Evaluation

Testing if the previous output contains the string get_vocab: True