Dontopedia

Llama 2

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-05.)

Llama 2 has 11 facts recorded in Dontopedia across 3 references, with 1 live disagreement.

11 facts·8 predicates·3 sources·1 in dispute

Mostly:rdf:type(3), has parameter count(1), compared with(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (4)

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.

comparedToCompared to(1)

comparedWithCompared With(1)

includesIncludes(1)

trainedModelTrained Model(1)

Other facts (10)

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.

10 facts
PredicateValueRef
Rdf:typeMachine Learning Model[1]
Rdf:typeSelf Hosted Llm[2]
Rdf:typeSelf Hosted Llm[3]
Has Parameter Count13000000000[1]
Compared WithFalcon[1]
Evaluated onTest Dataset[1]
Has TokenizerFalcon Tokenizer[1]
Compared toFalcon[1]
Parameter Size13B[1]
Is Example ofSelf Hosted Llm[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.

hasParameterCountbeam/eeee12e5-48f7-4435-bf8a-e4edf5c6c9c2
13000000000
typebeam/eeee12e5-48f7-4435-bf8a-e4edf5c6c9c2
ex:MachineLearningModel
comparedWithbeam/eeee12e5-48f7-4435-bf8a-e4edf5c6c9c2
ex:falcon
evaluatedOnbeam/eeee12e5-48f7-4435-bf8a-e4edf5c6c9c2
ex:test-dataset
hasTokenizerbeam/eeee12e5-48f7-4435-bf8a-e4edf5c6c9c2
ex:falcon-tokenizer
comparedTobeam/eeee12e5-48f7-4435-bf8a-e4edf5c6c9c2
ex:falcon
parameterSizebeam/eeee12e5-48f7-4435-bf8a-e4edf5c6c9c2
13B
typebeam/3a2f3fcc-2602-4982-ac71-4e34f2be1877
ex:SelfHostedLLM
typebeam/f5ccca0f-5f03-47b2-93f1-d6f2f4ac4189
ex:SelfHostedLLM
isExampleOfbeam/f5ccca0f-5f03-47b2-93f1-d6f2f4ac4189
ex:self-hosted-llm
labelbeam/f5ccca0f-5f03-47b2-93f1-d6f2f4ac4189
Llama 2

References (3)

3 references
  1. ctx:claims/beam/eeee12e5-48f7-4435-bf8a-e4edf5c6c9c2
    • full textbeam-chunk
      text/plain1 KBdoc:beam/eeee12e5-48f7-4435-bf8a-e4edf5c6c9c2
      Show excerpt
      tokenizer=falcon_tokenizer, ) # Train the models trainer_llama.train() trainer_falcon.train() # Evaluate the models results_llama = trainer_llama.evaluate(test_dataset) results_falcon = trainer_falcon.evaluate(test_dataset) print(f"L
  2. ctx:claims/beam/3a2f3fcc-2602-4982-ac71-4e34f2be1877
    • full textbeam-chunk
      text/plain1 KBdoc:beam/3a2f3fcc-2602-4982-ac71-4e34f2be1877
      Show excerpt
      - **Rate Limit Headers**: Check if the API provides headers indicating the remaining rate limit and reset time. This can help you dynamically adjust your request rate. - **Concurrency**: If appropriate, use concurrency techniques (e.g., thr
  3. ctx:claims/beam/f5ccca0f-5f03-47b2-93f1-d6f2f4ac4189

See also

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