Dontopedia

tokenizer = AutoTokenizer.from_pretrained(model_name)

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tokenizer = AutoTokenizer.from_pretrained(model_name) has 13 facts recorded in Dontopedia across 3 references, with 2 live disagreements.

13 facts·8 predicates·3 sources·2 in dispute

Mostly:rdf:type(3), has keyword argument(3), function name(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (1)

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containsFunctionCallContains Function Call(1)

Other facts (12)

The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.

12 facts
PredicateValueRef
Rdf:typeFunction Call[1]
Rdf:typeTokenizer Creation[2]
Rdf:typeCode Statement[3]
Has Keyword ArgumentPrefix Search Arg[1]
Has Keyword ArgumentSuffix Search Arg[1]
Has Keyword ArgumentInfix Finditer Arg[1]
Function NameTokenizer[1]
Assigns toCustom Tokenizer[1]
Has ArgumentNlp Vocab[1]
Uses Model NameDistilbert Base Multilingual Cased[2]
Output VariableTokenizer[2]
Uses ClassAuto Tokenizer[3]

Timeline

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

typebeam/18306c1f-b51a-45dd-b169-e340e3696b52
ex:FunctionCall
functionNamebeam/18306c1f-b51a-45dd-b169-e340e3696b52
Tokenizer
assignsTobeam/18306c1f-b51a-45dd-b169-e340e3696b52
ex:custom_tokenizer
hasArgumentbeam/18306c1f-b51a-45dd-b169-e340e3696b52
ex:nlp-vocab
hasKeywordArgumentbeam/18306c1f-b51a-45dd-b169-e340e3696b52
ex:prefix-search-arg
hasKeywordArgumentbeam/18306c1f-b51a-45dd-b169-e340e3696b52
ex:suffix-search-arg
hasKeywordArgumentbeam/18306c1f-b51a-45dd-b169-e340e3696b52
ex:infix-finditer-arg
typebeam/20f0272f-7b57-4162-9e25-c21ae614367b
ex:TokenizerCreation
usesModelNamebeam/20f0272f-7b57-4162-9e25-c21ae614367b
ex:distilbert-base-multilingual-cased
outputVariablebeam/20f0272f-7b57-4162-9e25-c21ae614367b
ex:tokenizer
typebeam/d3dd63ff-b7e5-4717-8f41-9969d9f06a45
ex:CodeStatement
labelbeam/d3dd63ff-b7e5-4717-8f41-9969d9f06a45
tokenizer = AutoTokenizer.from_pretrained(model_name)
usesClassbeam/d3dd63ff-b7e5-4717-8f41-9969d9f06a45
ex:AutoTokenizer

References (3)

3 references
  1. ctx:claims/beam/18306c1f-b51a-45dd-b169-e340e3696b52
    • full textbeam-chunk
      text/plain1 KBdoc:beam/18306c1f-b51a-45dd-b169-e340e3696b52
      Show excerpt
      Now, let's tokenize some text and visualize the process for debugging. ```python # Sample text text = "Hello, world! This is a test sentence with [custom] tokens." # Process the text doc = nlp(text) # Print the tokens for token in doc:
  2. ctx:claims/beam/20f0272f-7b57-4162-9e25-c21ae614367b
    • full textbeam-chunk
      text/plain1 KBdoc:beam/20f0272f-7b57-4162-9e25-c21ae614367b
      Show excerpt
      train_text, test_text, train_labels, test_labels = train_test_split(df['text'], df['label'], test_size=0.2, random_state= 42) # Load a pre-trained multi-language model model_name = 'distilbert-base-multilingual-cased' tokenizer = AutoToken
  3. ctx:claims/beam/d3dd63ff-b7e5-4717-8f41-9969d9f06a45

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