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--- |
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license: apache-2.0 |
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pipeline_tag: text-generation |
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language: |
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- en |
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- he |
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tags: |
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- pretrained |
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inference: |
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parameters: |
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temperature: 0.7 |
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--- |
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[<img src="https://i.ibb.co/5Lbwyr1/dicta-logo.jpg" width="300px"/>](https://dicta.org.il) |
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# Adapting LLMs to Hebrew: Unveiling DictaLM 2.0 with Enhanced Vocabulary and Instruction Capabilities |
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The DictaLM-2.0 Large Language Model (LLM) is a pretrained generative text model with 7 billion parameters trained to specialize in Hebrew text. |
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For full details of this model please read our [release blog post](https://dicta.org.il/dicta-lm) or the [technical report](https://arxiv.org/abs/2407.07080). |
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This is the base model designed for completion (not for chat!) in the GGUF format for use with llama.cpp. |
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There are two versions available - float16 precision (`*.F16.gguf`) and 4-bit quantized precision (`*.Q4_K_M.gguf`). |
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You can view and access the full collection of base/instruct unquantized/quantized versions of `DictaLM-2.0` [here](https://huggingface.co/collections/dicta-il/dicta-lm-20-collection-661bbda397df671e4a430c27). |
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## Model Architecture |
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DictaLM-2.0 is based on the [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) model with the following changes: |
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- An extended tokenizer with 1,000 injected tokens specifically for Hebrew, increasing the compression rate from 5.78 tokens/word to 2.76 tokens/word. |
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- Continued pretraining on over 190B tokens of naturally occuring text, 50% Hebrew and 50% English. |
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## Notice |
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DictaLM 2.0 is a pretrained base model and therefore does not have any moderation mechanisms. |
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## Citation |
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If you use this model, please cite: |
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```bibtex |
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@misc{shmidman2024adaptingllmshebrewunveiling, |
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title={Adapting LLMs to Hebrew: Unveiling DictaLM 2.0 with Enhanced Vocabulary and Instruction Capabilities}, |
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author={Shaltiel Shmidman and Avi Shmidman and Amir DN Cohen and Moshe Koppel}, |
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year={2024}, |
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eprint={2407.07080}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL}, |
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url={https://arxiv.org/abs/2407.07080}, |
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} |
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``` |
