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Skip Special Tokens Argument

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-11.)

Skip Special Tokens Argument has 10 facts recorded in Dontopedia across 3 references, with 2 live disagreements.

10 facts·7 predicates·3 sources·2 in dispute

Mostly:rdf:type(3), rdfs:label(2), has value(1)

Maturity scale raw canonical shape-checked rule-derived certified

Rdf:typein disputerdf:type

Rdfs:labelin disputerdfs:label

  • skip_special_tokens=True[2]all time · 7472272b 494d 4a2b Bd12 F0166287b4bc
  • skip_special_tokens[3]sourceall time · D3dd63ff B7e5 4717 8f41 9969d9f06a45

Has ValuehasValue

  • true[3]sourceall time · D3dd63ff B7e5 4717 8f41 9969d9f06a45

Removesremoves

Causescauses

Valuevalue

  • true[1]sourceall time · 6b6ba1ac Fc7c 459c B11d Ac6297a6941b

Functionfunction

Inbound mentions (2)

Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.

hasParameterHas Parameter(2)

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.

10 undated
—
causesbeam/6b6ba1ac-fc7c-459c-b11d-ac6297a6941b
ex:special-tokens-removal
—
functionbeam/7472272b-494d-4a2b-bd12-f0166287b4bc
ex:removes-special-tokens
—
hasValuebeam/d3dd63ff-b7e5-4717-8f41-9969d9f06a45
true
—
labelbeam/7472272b-494d-4a2b-bd12-f0166287b4bc
skip_special_tokens=True
—
labelbeam/d3dd63ff-b7e5-4717-8f41-9969d9f06a45
skip_special_tokens
—
typebeam/6b6ba1ac-fc7c-459c-b11d-ac6297a6941b
ex:Argument
—
typebeam/d3dd63ff-b7e5-4717-8f41-9969d9f06a45
ex:Argument
—
typebeam/7472272b-494d-4a2b-bd12-f0166287b4bc
ex:MethodArgument
—
removesbeam/6b6ba1ac-fc7c-459c-b11d-ac6297a6941b
ex:special-tokens
—
valuebeam/6b6ba1ac-fc7c-459c-b11d-ac6297a6941b
true

References (3)

3 references
  1. [1]beam-chunk4 facts
    customctx:claims/beam/6b6ba1ac-fc7c-459c-b11d-ac6297a6941b
    • full textbeam-chunk
      text/plain1 KBdoc:beam/6b6ba1ac-fc7c-459c-b11d-ac6297a6941b
      Show excerpt
      - The generated output is decoded back into a human-readable format using the `tokenizer.decode` method. The `skip_special_tokens=True` argument removes special tokens that are not part of the final answer. By providing detailed respons…
  2. [2]beam-chunk3 facts
    customctx:claims/beam/7472272b-494d-4a2b-bd12-f0166287b4bc
    • full textbeam-chunk
      text/plain1 KBdoc:beam/7472272b-494d-4a2b-bd12-f0166287b4bc
      Show excerpt
      - The `model.generate` method is used to generate the answer based on the tokenized input. The `with torch.no_grad()` context manager disables gradient calculation, which is not needed during inference and helps save memory. 4. **Decodi…
  3. [3]beam-chunk3 facts
    customctx:claims/beam/d3dd63ff-b7e5-4717-8f41-9969d9f06a45
    • full textbeam-chunk
      text/plain1 KBdoc:beam/d3dd63ff-b7e5-4717-8f41-9969d9f06a45
      Show excerpt
      tokenizer = AutoTokenizer.from_pretrained(model_name) # Define the LLM call function with batch processing and parallel execution def llm_call(queries, batch_size=100, num_workers=4): # Process queries in batches processed_outputs …

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