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--- |
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datasets: |
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- agentlans/crash-course |
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base_model: |
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- google/gemma-2-9b-it |
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- FuseAI/FuseChat-Gemma-2-9B-Instruct |
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- jsgreenawalt/gemma-2-9B-it-advanced-v2.1 |
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tags: |
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- gemma2 |
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language: |
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- en |
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pipeline_tag: text-generation |
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license: gemma |
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--- |
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# Gemma2-9B-AdvancedFuse |
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Gemma2-9B-AdvancedFuse is an experimental, open-source large language model (LLM) with 9 billion parameters. |
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It aims to combine the strengths of [FuseAI/FuseChat-Gemma-2-9B-Instruct](https://huggingface.co/fuseai/fusechat-gemma-2-9b-instruct) and |
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[jsgreenawalt/gemma-2-9B-it-advanced-v2.1](https://huggingface.co/jsgreenawalt/gemma-2-9b-it-advanced-v2.1) through additive linear merging, |
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further fine-tuned on a 12K row dataset from [agentlans/crash-course](https://huggingface.co/datasets/agentlans/crash-course) |
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for enhanced chat and instruct performance, including math and multilingual prompts. |
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## Capabilities |
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- **Text Generation:** Generates coherent emails, summaries, and notes. This model card was primarily generated by the model itself. |
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- **Instruction Following:** Demonstrates strong ability to understand and execute instructions in conversational settings. |
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- **Roleplaying:** Can engage in third-person narrative roleplay but may exhibit common GPT expressions or clichés. |
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### Limitations |
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As with most large language models: |
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- **Factual Errors:** May generate incorrect or outdated information due to data biases. |
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- **Mathematical Operations:** Struggles with mathematical calculations requiring symbolic reasoning despite its finetuning data. |
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- **Handling Unsafe Input:** May generate unsafe, biased, or malicious content if provided inappropriate input. Careful prompt engineering is recommended. |
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### Model Usage Guidelines |
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1. Use clear and specific instructions for optimal performance. |
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2. Verify generated outputs for factual accuracy when critical information is involved. |
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3. Avoid providing inputs that could lead to harmful or unethical responses. |
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4. Consider using human review, especially in high-stakes applications. |
