Model Type | Transformer, Autoregressive Language Model |
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Use Cases |
Areas: | Research, Academic Benchmarks |
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Limitations: | Can generate harmful or sensitive content without proper safety filtering., Inaccuracies in generated statements; facts need verification. |
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Supported Languages | |
Training Details |
Data Sources: | OLMo-Mix-1124, Dolmino-Mix-1124 |
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Data Volume: | 5 Trillion (Stage 1) & 843B (Stage 2) tokens |
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Responsible Ai Considerations |
Fairness: | Models can generate harmful and sensitive content if not properly managed. |
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Mitigation Strategies: | Users advised to consider risks of misuse. |
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Input Output |
Input Format: | AutoTokenizer: Tokenized input. |
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Accepted Modalities: | |
Output Format: | |
Performance Tips: | Using CUDA and quantization can enhance performance. |
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