52 lines
2.0 KiB
Markdown
52 lines
2.0 KiB
Markdown
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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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```
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