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Lightweight language model based on Gemma2 2B created by merging multiple fine tuned Gemma2-2B-IT versions to test multilingual conversation capabilities in specialized low parameter language models.
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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This model was merged using the [Model Stock](https://arxiv.org/abs/2403.19522) merge method using [google/gemma-2-2b-it](https://huggingface.co/google/gemma-2-2b-it) as a base.
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* [VAGOsolutions/SauerkrautLM-gemma-2-2b-it](https://huggingface.co/VAGOsolutions/SauerkrautLM-gemma-2-2b-it)
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* [stvlynn/Gemma-2-2b-Chinese-it](https://huggingface.co/stvlynn/Gemma-2-2b-Chinese-it)
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The following YAML configuration was used to produce this model:
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```
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### Usage
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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Lightweight language model based on Gemma2 2B created by merging multiple fine tuned Gemma2-2B-IT versions to test multilingual conversation capabilities in specialized low parameter language models.
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## Models Merged
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This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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This model was merged using the [Model Stock](https://arxiv.org/abs/2403.19522) merge method using [google/gemma-2-2b-it](https://huggingface.co/google/gemma-2-2b-it) as a base.
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* [VAGOsolutions/SauerkrautLM-gemma-2-2b-it](https://huggingface.co/VAGOsolutions/SauerkrautLM-gemma-2-2b-it)
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* [stvlynn/Gemma-2-2b-Chinese-it](https://huggingface.co/stvlynn/Gemma-2-2b-Chinese-it)
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## 🧩 Configuration
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The following YAML configuration was used to produce this model:
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```
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### 💻 Usage
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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