| Model Type | | text generation, conversational, instruction following, reasoning, function calling |
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| Use Cases |
| Areas: | | research, commercial applications |
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| Applications: | | instruction following, knowledge-driven QA, reasoning, truthful answer generation, function calling, generalist applications |
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| Primary Use Cases: | | instruction-following, knowledge-driven QA benchmarks, reasoning, function-calling |
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| Additional Notes | | Llama-3.1-Storm-8B merges fine-tuned model with Llama-Spark using SLERP to improve characteristics. |
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| Supported Languages | | en (English), de (German), fr (French), it (Italian), pt (Portuguese), hi (Hindi), es (Spanish), th (Thai) |
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| Training Details |
| Data Sources: | |
| Data Volume: | | ~1 million examples selected from ~2.8 million |
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| Methodology: | | Self-Curation, Spectrum-based targeted fine-tuning, SLERP model merging |
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| Input Output |
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| Release Notes |
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| Notes: | | Introduction of GGUF quantized version for use with llama.cpp |
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