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@@ -24,7 +24,7 @@ Eurydice 24b v2c is built on an enhanced dataset than the previous version & is
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  - **Model type:** Causal Language Model
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  - **Language(s):** English (primarily), may support other languages
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  - **License:** Apache 2.0
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- - **Repository:** https://huggingface.co/aixonlab/Eurydice-24b-v2c
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  ## Quantization
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  - **GGUF:** Coming Soon !
@@ -39,10 +39,10 @@ Eurydice 24b v2c is built on an enhanced dataset than the previous version & is
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  As an advanced language model for various natural language processing tasks, including but not limited to text generation (excels in chat), question-answering, and analysis.
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  ## Ethical Considerations 🤔
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- As a model based on multiple sources, Eurydice 24b v2c may inherit biases and limitations from its constituent models. Users should be aware of potential biases in generated content and use the model responsibly.
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  ## Performance and Evaluation
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- Performance metrics and evaluation results for Eurydice 24b v2c are yet to be determined. Users are encouraged to contribute their findings and benchmarks.
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  ## Limitations and Biases
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  The model may exhibit biases present in its training data and constituent models. It's crucial to critically evaluate the model's outputs and use them in conjunction with human judgment.
 
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  - **Model type:** Causal Language Model
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  - **Language(s):** English (primarily), may support other languages
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  - **License:** Apache 2.0
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+ - **Repository:** https://huggingface.co/aixonlab/Eurydice-24b-v1c
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  ## Quantization
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  - **GGUF:** Coming Soon !
 
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  As an advanced language model for various natural language processing tasks, including but not limited to text generation (excels in chat), question-answering, and analysis.
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  ## Ethical Considerations 🤔
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+ As a model based on multiple sources, Eurydice 24b v1c may inherit biases and limitations from its constituent models. Users should be aware of potential biases in generated content and use the model responsibly.
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  ## Performance and Evaluation
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+ Performance metrics and evaluation results for Eurydice 24b v1c are yet to be determined. Users are encouraged to contribute their findings and benchmarks.
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  ## Limitations and Biases
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  The model may exhibit biases present in its training data and constituent models. It's crucial to critically evaluate the model's outputs and use them in conjunction with human judgment.