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* add new bloom classes * (feat) add bloom classification tests; make style * style: change import in test * add some typehints to bloom classes * merge main into branch * fix: input checking in bloom seq classification * fix tests * change model class tests * fix few tests - more tests should pass - one test left * make token classifier return hidden states * style: make BLOOM typehints consistent Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com> Co-authored-by: younesbelkada <younesbelkada@gmail.com> Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
57 lines
1.9 KiB
Plaintext
57 lines
1.9 KiB
Plaintext
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# BLOOM
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## Overview
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The BLOOM model has been proposed with its various versions through the [BigScience Workshop](https://bigscience.huggingface.co/). BigScience is inspired by other open science initiatives where researchers have pooled their time and resources to collectively achieve a higher impact.
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The architecture of BLOOM is essentially similar to GPT3 (auto-regressive model for next token prediction), but has been trained on different 46 languages including code.
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Several smaller versions of the models have been trained on the same dataset. BLOOM is available in the following versions:
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- [bloom-350m](https://huggingface.co/bigscience/bloom-350m)
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- [bloom-760m](https://huggingface.co/bigscience/bloom-760m)
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- [bloom-1b3](https://huggingface.co/bigscience/bloom-1b3)
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- [bloom-2b5](https://huggingface.co/bigscience/bloom-2b5)
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- [bloom-6b3](https://huggingface.co/bigscience/bloom-6b3)
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- [bloom](https://huggingface.co/bigscience/bloom) (175B parameters)
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## BloomConfig
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[[autodoc]] BloomConfig
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- all
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## BloomModel
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[[autodoc]] BloomModel
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- forward
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## BloomTokenizerFast
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[[autodoc]] BloomTokenizerFast
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- all
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## BloomForCausalLM
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[[autodoc]] BloomForCausalLM
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- forward
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## BloomForSequenceClassification
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[[autodoc]] BloomForSequenceClassification
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- forward
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## BloomForTokenClassification
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[[autodoc]] BloomForTokenClassification
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- forward |