BLOOM training dataset:Bloom Library

Bloom Library

Bloom Library

由CLeong著作·2022·被引用17次—WepresentBloomLibrary,alinguisticallydiversesetofmultimodalandmultilingualdatasetsforlanguagemodeling,imagecaptioning,visualstorytelling,and ...。其他文章還包含有:「bigsciencebloom」、「BLOOM(languagemodel)」、「BLOOM:A176B」、「ExploringBLOOM」、「lju」、「sil」、「sil-aibloom」、「StepbyStepGuidetoFine」

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LLM BLOOM 下載BLOOM modelBloom github
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bigsciencebloom
bigsciencebloom

https://huggingface.co

BLOOM is an autoregressive Large Language Model (LLM), trained to continue text from a prompt on vast amounts of text data using industrial-scale computational ...

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BLOOM (language model)
BLOOM (language model)

https://en.wikipedia.org

It encompasses 46 natural languages (in amounts ranging from 30% of the whole dataset for English to 0.00002% for Chi Tumbuka) and 13 programming languages.

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BLOOM: A 176B
BLOOM: A 176B

https://sh-tsang.medium.com

1.2. ROOTS: Training Dataset · Left: A treemap plot of the language families of all 46 natural languages where surface is proportional to the ...

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Exploring BLOOM
Exploring BLOOM

https://www.datacamp.com

Dive into BLOOM, a multilingual large language model, exploring its creation, technical specs, usage, and ethical aspects for democratizing AI.

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lju
lju

https://github.com

We use the Kaggle Olympics Data Set for this example. Specifically, the dataset contains information from the Summer and Winter Olympics from 1896 to 2016.

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sil
sil

https://huggingface.co

This version of the Bloom Library data is developed specifically for the language modeling task. It includes data from 364 languages across 31 language ...

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sil-aibloom
sil-aibloom

https://github.com

training scripts for the bloom-speech dataset. Contribute to sil-ai/bloom-speech-training development by creating an account on GitHub.

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Step by Step Guide to Fine
Step by Step Guide to Fine

https://docs.e2enetworks.com

The training dataset should be a collection of text examples that are relevant to the task. The following steps can be followed to fine-tune BLOOM: * Install ...