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 |
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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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