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* Fix documentation for Gemma2. Model sizes and Blog post URL are wrong in the documentation. * Update docs/source/en/model_doc/gemma2.md Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com> --------- Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
59 lines
2.2 KiB
Markdown
59 lines
2.2 KiB
Markdown
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<!--Copyright 2024 The HuggingFace Team. All rights reserved.
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Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with
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the License. You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on
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specific language governing permissions and limitations under the License.
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⚠️ Note that this file is in Markdown but contain specific syntax for our doc-builder (similar to MDX) that may not be
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# Gemma2
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## Overview
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The Gemma2 model was proposed in [Gemma2: Open Models Based on Gemini Technology and Research](https://blog.google/technology/developers/google-gemma-2/) by Gemma2 Team, Google.
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Two Gemma2 models are released, with parameters sizes of 9 billion (9B) and 27 billion (27B).
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The abstract from the blog post is the following:
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*Now we’re officially releasing Gemma 2 to researchers and developers globally. Available in both 9 billion (9B) and 27 billion (27B) parameter sizes, Gemma 2 is higher-performing and more efficient at inference than the first generation, with significant safety advancements built in. In fact, at 27B, it offers competitive alternatives to models more than twice its size, delivering the kind of performance that was only possible with proprietary models as recently as December.*
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Tips:
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- The original checkpoints can be converted using the conversion script `src/transformers/models/Gemma2/convert_Gemma2_weights_to_hf.py`
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This model was contributed by [Arthur Zucker](https://huggingface.co/ArthurZ), [Pedro Cuenca](https://huggingface.co/pcuenq) and [Tom Arsen]().
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## Gemma2Config
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[[autodoc]] Gemma2Config
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## Gemma2Model
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[[autodoc]] Gemma2Model
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- forward
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## Gemma2ForCausalLM
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[[autodoc]] Gemma2ForCausalLM
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- forward
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## Gemma2ForSequenceClassification
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[[autodoc]] Gemma2ForSequenceClassification
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- forward
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## Gemma2ForTokenClassification
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[[autodoc]] Gemma2ForTokenClassification
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- forward
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