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README.md
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library_name: transformers
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tags:
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- text-generation-inference
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---
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3. **Dependency on Prompt Quality**: The quality of the model’s output heavily relies on the clarity and specificity of the input prompt. Poorly framed prompts may lead to irrelevant or incomplete responses.
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4. **Long Context Handling**: While it is designed for long-chain reasoning, performance may degrade with excessively long inputs or contexts, resulting in loss of coherence or incomplete reasoning.
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5. **Resource Requirements**: Due to its large size (27 billion parameters), it requires substantial computational resources for both inference and fine-tuning, limiting its accessibility for users without high-performance hardware.
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6. **Language Support**: Although it excels in English, its capabilities in other languages may be limited, and unexpected issues may arise when processing multilingual or code-mixed inputs.
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library_name: transformers
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tags:
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- text-generation-inference
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- Gemma
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---
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3. **Dependency on Prompt Quality**: The quality of the model’s output heavily relies on the clarity and specificity of the input prompt. Poorly framed prompts may lead to irrelevant or incomplete responses.
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| 122 |
4. **Long Context Handling**: While it is designed for long-chain reasoning, performance may degrade with excessively long inputs or contexts, resulting in loss of coherence or incomplete reasoning.
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| 123 |
5. **Resource Requirements**: Due to its large size (27 billion parameters), it requires substantial computational resources for both inference and fine-tuning, limiting its accessibility for users without high-performance hardware.
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| 124 |
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6. **Language Support**: Although it excels in English, its capabilities in other languages may be limited, and unexpected issues may arise when processing multilingual or code-mixed inputs.
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