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--- |
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library_name: transformers |
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license: llama3.1 |
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datasets: |
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- ctu-aic/cs_instruction_tuning_collection |
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- ctu-aic/en_instruction_tuning_collection |
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language: |
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- cs |
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- en |
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- de |
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- fr |
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- it |
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- pt |
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- hi |
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- es |
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- th |
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base_model: |
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- meta-llama/Llama-3.1-8B-Instruct |
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pipeline_tag: text-generation |
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tags: |
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- Unsloth |
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- model adaptation |
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- NLI |
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--- |
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# Model Card for Llama 3.1 8B Instruct -> IT_(cs+en) |
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<!-- Provide a quick summary of what the model is/does. --> |
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Llama 3.1 8B Instruct instruction-tuned using a mixture of cs_instruction_tuning_collection and en_instruction_tuning_collection. **More information in the thesis**: TBA. (The notation is thesis is: B+IT -> IT_(cs+en)) |
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<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/made with unsloth.png" width="200" align="center" /> |
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## 🛑 Ethical Considerations and Limitations |
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This model is a Czech-adapted version of Meta's LLaMA 3.1 8B Instruct, developed as part of master's thesis. It is intended solely for academic and research purposes. |
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- ⚠️ Not Intended for Production Use: This model has not undergone extensive safety testing, fine-tuning for alignment, or robust filtering of harmful outputs. Do not deploy this model in any application or setting that impacts users or the public. |
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- ❗ Potential for Harm: The model may generate biased, offensive, false, or otherwise harmful content. It does not include safeguards such as moderation layers or toxicity detection. |
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- 🧪 Experimental Nature: This model is an academic experiment accompanying a thesis project and may contain unintended behaviors or limitations due to limited training data, resources, or evaluation. |
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- 👤 Responsibility: Any use of this model is at the user’s own risk. The author does not assume responsibility for any consequences arising from the use of the model. |
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- 🔒 Respect for Original License: This adaptation is subject to the original terms and conditions set by Meta for LLaMA models. |
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Researchers and practitioners using this model must ensure appropriate ethical oversight and conduct rigorous evaluations before any further deployment or fine-tuning. |
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## Citation |
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TBA |
