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Boldt
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Boldt-DC-1B

Text Generation
Transformers
Safetensors
German
llama
nlp
custom_code
german
text-generation-inference
Model card Files
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@@ -83,9 +83,10 @@ Despite being trained on substantially fewer tokens, the Boldt-1B family outperf
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  | Model | Tokens | MMLU | ARC-C | ARC-E | H-Swag | LAMBADA | OBQA | Avg. |
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  | :--- | :--- | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
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  | [EuroLLM-1.7B](https://huggingface.co/utter-project/EuroLLM-1.7B) | 4T* | 31.04 | 31.58 | 54.68 | 45.30 | 44.52 | 50.50 | 42.94 |
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- | [Qwen3-1.7B-Base](https://huggingface.co/Qwen/Qwen3-1.7B-Base) | 36T* | **34.17** | **37.49** | 57.00 | 45.20 | 49.81 | 45.66 | 44.89 |
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  | [BübleLM-2B](https://huggingface.co/flair/bueble-lm-2b) | 2T* | 29.68 | 32.62 | 53.63 | 46.57 | 43.55 | 49.70 | 42.63 |
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- | [Gemma-2-2B](https://huggingface.co/google/gemma-2-2b) | 2T* | 33.99 | 37.11 | **57.47** | **49.62** | **52.64** | **48.89** | **46.62** |
 
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  ## Safety & Ethics
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  | Model | Tokens | MMLU | ARC-C | ARC-E | H-Swag | LAMBADA | OBQA | Avg. |
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  | :--- | :--- | :--- | :--- | :--- | :--- | :--- | :--- | :--- |
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  | [EuroLLM-1.7B](https://huggingface.co/utter-project/EuroLLM-1.7B) | 4T* | 31.04 | 31.58 | 54.68 | 45.30 | 44.52 | 50.50 | 42.94 |
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+ | [Qwen3-1.7B-Base](https://huggingface.co/Qwen/Qwen3-1.7B-Base) | 36T* | 34.17 | 37.49 | 57.00 | 45.20 | 49.81 | 45.66 | 44.89 |
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  | [BübleLM-2B](https://huggingface.co/flair/bueble-lm-2b) | 2T* | 29.68 | 32.62 | 53.63 | 46.57 | 43.55 | 49.70 | 42.63 |
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+ | [Gemma-2-2B](https://huggingface.co/google/gemma-2-2b) | 2T* | 33.99 | 37.11 | 57.47 | 49.62 | 52.64 | 48.89 | 46.62 |
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+ | [Gemma-4-E2B](https://huggingface.co/google/gemma-4-E2B) | N/A | **34.48** | **41.14** | **63.16** | **55.22** | **55.96** | **50.51** | **50.08** |
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  ## Safety & Ethics
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