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README.md
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- **Paper:** https://arxiv.org/abs/2302.13971 (LLaMA 3)
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- **Demo:** [Example usage with llama-cli]
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## Uses
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### Direct Use
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- Chatbots for general conversation
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- Instruction-following NLP tasks
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- Generating structured or unstructured text
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- Educational assistants or question answering
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### Downstream Use
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- Fine-tuning for task-specific NLP tasks
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- Integration into larger applications such as AI assistants or virtual agents
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### Out-of-Scope Use
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- Should not be used for high-stakes decision-making (medical, legal, or financial advice)
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- May generate biased, unsafe, or incorrect outputs if unchecked
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## Bias, Risks, and Limitations
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- Model reflects biases present in its training dataset.
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- May generate unsafe or offensive outputs if prompted maliciously.
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- Performance may vary with non-English inputs unless pre-translated.
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### Recommendations
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- Always monitor outputs in deployment.
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- Use prompt filtering or moderation for sensitive domains.
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- Combine with human-in-the-loop evaluation for critical tasks.
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## How to Get Started with the Model
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```bash
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llama-cli --model meta-llama-3.1-8b-alpaca.Q4_K_M.gguf -p "Hello Eliza"
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```
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## Training Details
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### Training Data
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year={2025},
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howpublished={\url{https://huggingface.co/unsloth/meta-llama-3.1-8b-alpaca}}
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}
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```
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**APA:**
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Anezatra. (2025). *LLaMA 3 8B Alpaca Fine-Tuned Model.* HuggingFace. https://huggingface.co/unsloth/meta-llama-3.1-8b-alpaca
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## Glossary
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- **LoRA:** Low-Rank Adaptation for efficient fine-tuning
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- **GGUF:** Quantized model format compatible with llama.cpp
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- **bf16:** Brain Floating Point 16-bit precision
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- **Q4_K_M:** Quantization method for reduced memory footprint
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## Model Card Authors
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- Anezatra
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## Model Card Contact
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- HuggingFace: https://huggingface.co/unsloth
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- Email: [email protected]
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- **Paper:** https://arxiv.org/abs/2302.13971 (LLaMA 3)
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- **Demo:** [Example usage with llama-cli]
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## Training Details
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### Training Data
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year={2025},
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howpublished={\url{https://huggingface.co/unsloth/meta-llama-3.1-8b-alpaca}}
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}
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```
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