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knowledge/technology/large_language_model/granite/attribution.txt
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Title of work: IBM Granite | ||
Link to work: https://en.wikipedia.org/wiki/IBM_Granite | ||
Revision: https://en.wikipedia.org/wiki/IBM_Granite&oldid=1246833397 | ||
License of the work: CC-BY-SA-4.0 | ||
Creator names: Wikipedia Authors |
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knowledge/technology/large_language_model/granite/qna.yaml
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created_by: cmizurichibmcom | ||
version: 3 | ||
domain: large-language-model | ||
document_outline: Knowledge contribution about the IBM Granite model | ||
seed_examples: | ||
- context: >- | ||
IBM Granite is a series of decoder-only Al foundation models created by | ||
IBM. It was announced on September 7, 2023, and an initial paper was | ||
published 4 days later. | ||
questions_and_answers: | ||
- question: What is IBM Granite | ||
answer: >- | ||
IBM Granite is a series of decoder-only Al foundation models created | ||
by IBM. | ||
- question: When was IBM Granite announced? | ||
answer: September 7, 2023 | ||
- question: What's a series of IBM decoder-only Al foundation models? | ||
answer: IBM Granite | ||
- context: >- | ||
==Foundation models== | ||
A foundation model is an AI model trained on broad data at scale such that | ||
it can be adapted to a wide range of downstream tasks. | ||
Granite's first foundation models were Granite.13b.instruct and | ||
Granite.13b.chat. The "13b" in their name comes from 13 billion, the | ||
amount of parameters they have as models, lesser than most of the larger | ||
models of the time. Later models vary from 3 to 34 billion parameters. | ||
On May 6, 2024, IBM released the source code of four variations of Granite | ||
Code Models under Apache 2, an open source permissive license that allows | ||
completely free use, modification and sharing of the software, and put | ||
them on Hugging Face for public use. According to IBM's own report, | ||
Granite 8b outperforms Llama 3 on several coding related tasks within | ||
similar range of parameters. | ||
questions_and_answers: | ||
- question: What is a foundation model? | ||
answer: >- | ||
A foundation model is an AI model trained on broad data at scale, | ||
making it adaptable to a wide range of downstream tasks. | ||
- question: >- | ||
What are the names of the first foundation models in the Granite | ||
series? | ||
answer: The first models were Granite.13b.instruct and Granite.13b.chat. | ||
- question: What does the "13b" in Granite.13b.instruct refer to? | ||
answer: The "13b" refers to the 13 billion parameters in the model. | ||
- context: >- | ||
'''IBM Granite''' is a series of decoder-only [[AI]] [[foundation | ||
model|foundation models]] created by [[IBM]]. It was announced on | ||
September 7, 2023. | ||
==Foundation models== | ||
A foundation model is an AI model trained on broad data at scale such that | ||
it can be adapted to a wide range of downstream tasks. | ||
Granite's first foundation models were Granite.13b.instruct and | ||
Granite.13b.chat. The "13b" in their name comes from 13 billion, the | ||
amount of parameters they have as models, lesser than most of the larger | ||
models of the time. Later models vary from 3 to 34 billion parameters. | ||
On May 6, 2024, IBM released the source code of four variations of Granite | ||
Code Models under Apache 2, an open source permissive license that allows | ||
completely free use, modification and sharing of the software, and put | ||
them on Hugging Face for public use. According to IBM's own report, | ||
Granite 8b outperforms Llama 3 on several coding related tasks within | ||
similar range of parameters. | ||
questions_and_answers: | ||
- question: What is a foundation model? | ||
answer: >- | ||
A foundation model is an AI model trained on broad data at scale, | ||
making it adaptable to a wide range of downstream tasks. | ||
- question: >- | ||
What are the names of the first foundation models in the Granite | ||
series? | ||
answer: The first models were Granite.13b.instruct and Granite.13b.chat. | ||
- question: What does the "13b" in Granite.13b.instruct refer to? | ||
answer: The "13b" refers to the 13 billion parameters in the model. | ||
- context: >- | ||
'''IBM Granite''' is a series of decoder-only created by [[IBM]]. It was | ||
announced on September 7, 2023. | ||
==Foundation models== | ||
A foundation model is an AI model trained on broad data at scale such that | ||
it can be adapted to a wide range of downstream tasks. | ||
Granite's first foundation models were Granite.13b.instruct and | ||
Granite.13b.chat. The "13b" in their name comes from 13 billion, the | ||
amount of parameters they have as models, lesser than most of the larger | ||
models of the time. Later models vary from 3 to 34 billion parameters. | ||
On May 6, 2024, IBM released the source code of four variations of Granite | ||
Code Models under Apache 2, an open source permissive license that allows | ||
completely free use, modification and sharing of the software, and put | ||
them on Hugging Face for public use. According to IBM's own report, | ||
Granite 8b outperforms Llama 3 on several coding related tasks within | ||
similar range of parameters. | ||
questions_and_answers: | ||
- question: How many model parameters do Granite models vary between? | ||
answer: Granite models vary from 3 billion to 34 billion parameters. | ||
- question: >- | ||
When did IBM release the source code for 4 variations of Granite Code | ||
Models? | ||
answer: IBM released the corresponding source code on May 6, 2024. | ||
- question: Under which license type did IBM release the Granite Code Models? | ||
answer: IBM released them under the Apache 2 open source license type. | ||
- context: >- | ||
IBM Granite is a series of decoder-only [[AI]] [[foundation | ||
model|foundation models]] created by [[IBM]]. It was announced on | ||
September 7, 2023. | ||
==Foundation models== | ||
A foundation model is an AI model trained on broad data at scale such that | ||
it can be adapted to a wide range of downstream tasks. | ||
Granite's first foundation models were Granite.13b.instruct and | ||
Granite.13b.chat. The "13b" in their name comes from 13 billion, the | ||
amount of parameters they have as models, lesser than most of the larger | ||
models of the time. Later models vary from 3 to 34 billion parameters. | ||
On May 6, 2024, IBM released the source code of four variations of Granite | ||
Code Models under Apache 2, an open source permissive license that allows | ||
completely free use, modification and sharing of the software, and put | ||
them on Hugging Face for public use. According to IBM's own report, | ||
Granite 8b outperforms Llama 3 on several coding related tasks within | ||
similar range of parameters. | ||
questions_and_answers: | ||
- question: Where did IBM make the Granite Code Models available for public use? | ||
answer: IBM made them available on Hugging Face. | ||
- question: >- | ||
What does the Apache 2 license allow users to do with the Granite Code | ||
Models? | ||
answer: >- | ||
The Apache 2 license allows free use, modification, and sharing of the | ||
software. | ||
- question: According to IBM, which model does Granite 8b outperform? | ||
answer: Granite 8b outperforms Llama 3 on several coding-related tasks. | ||
document: | ||
repo: https://github.com/cmizurichibmcom/taxonomy-knowledge-docs | ||
commit: d3ad06a9f47b426127533b0d3fc62a17b777d546 | ||
patterns: | ||
- IBM_Granite-20241021T104730005.md |