OLMo 7B Hf is an open-source language model by allenai. Features: 7b LLM, VRAM: 27.6GB, Context: 2K, License: apache-2.0, LLM Explorer Score: 0.2, Arc: 45.7, HellaSwag: 77.3, MMLU: 28.1, GSM8K: 3.8.
OLMo 7B Hf Parameters and Internals
| Model Type | | Transformer style autoregressive language model |
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| Use Cases |
| Areas: | | Research, Commercial applications |
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| Applications: | | Natural language processing tasks |
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| Primary Use Cases: | | Language modeling, Text generation |
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| Limitations: | | May produce harmful or biased content |
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| Considerations: | | User awareness of potential risks and limitations. |
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| Additional Notes | | Model checkpoints and code are open-source. |
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| Supported Languages | |
| Training Details |
| Data Sources: | |
| Data Volume: | | 2.5 Trillion Training Tokens |
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| Methodology: | | Sequential Block Transformer with SwiGLU activation and RoPE positional embeddings |
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| Context Length: | |
| Hardware Used: | | MI250X GPUs at LUMI supercomputer, A100-40GB GPUs provided by MosaicML |
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| Model Architecture: | | Transformer model with 32 layers, 4096 hidden size, 32 attention heads, sequential block type |
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| Safety Evaluation |
| Risk Categories: | | Harmful content, Sensitive content, Bias |
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| Ethical Considerations: | | Model can generate harmful and biased content. |
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| Responsible Ai Considerations |
| Fairness: | | Potential bias in language outputs. |
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| Transparency: | | Open-source model with accessible training data details. |
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| Accountability: | | Developed by Allen Institute for AI. |
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| Mitigation Strategies: | | Awareness of risks and user guidelines. |
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| Input Output |
| Input Format: | |
| Accepted Modalities: | |
| Output Format: | |
| Performance Tips: | | Use optimized settings for text generation speed and accuracy. |
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| Release Notes |
| Version: | |
| Notes: | | Initial release for open language modeling. |
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