DevsDoCode
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---
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language:
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- en
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license: apache-2.0
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library_name: transformers
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tags:
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- uncensored
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- transformers
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- llama
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- unsloth
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- llama-cpp
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- gguf-my-repo
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pipeline_tag: text-generation
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---
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brew install ggerganov/ggerganov/llama.cpp
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```
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Invoke the llama.cpp server or the CLI.
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CLI:
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llama-cli --hf-repo DevsDoCode/LLama-3-8b-Uncensored-Q5_K_S-GGUF --model llama-3-8b-uncensored.Q5_K_S.gguf -p "The meaning to life and the universe is"
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```
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```bash
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llama-server --hf-repo DevsDoCode/LLama-3-8b-Uncensored-Q5_K_S-GGUF --model llama-3-8b-uncensored.Q5_K_S.gguf -c 2048
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```
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Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
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---
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library_name: transformers
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tags:
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- llama-cpp
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- gguf-my-repo
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- uncensored
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- transformers
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- llama
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- unsloth
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- llama-cpp
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- gguf-my-repo
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language:
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- en
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license: apache-2.0
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pipeline_tag: text-generation
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---
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<div align="center">
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<!-- Replace `#` with your actual links -->
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<a href="https://youtube.com/@devsdocode"><img alt="YouTube" src="https://img.shields.io/badge/YouTube-FF0000?style=for-the-badge&logo=youtube&logoColor=white"></a>
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<a href="https://t.me/devsdocode"><img alt="Telegram" src="https://img.shields.io/badge/Telegram-2CA5E0?style=for-the-badge&logo=telegram&logoColor=white"></a>
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<a href="https://www.instagram.com/sree.shades_/"><img alt="Instagram" src="https://img.shields.io/badge/Instagram-E4405F?style=for-the-badge&logo=instagram&logoColor=white"></a>
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<a href="https://www.linkedin.com/in/developer-sreejan/"><img alt="LinkedIn" src="https://img.shields.io/badge/LinkedIn-0077B5?style=for-the-badge&logo=linkedin&logoColor=white"></a>
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<a href="https://buymeacoffee.com/devsdocode"><img alt="Buy Me A Coffee" src="https://img.shields.io/badge/Buy%20Me%20A%20Coffee-FFDD00?style=for-the-badge&logo=buymeacoffee&logoColor=black"></a>
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</div>
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## Crafted with ❤️ by Devs Do Code (Sree)
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### GGUF Technical Specifications
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Delve into the intricacies of GGUF, a meticulously crafted format that builds upon the robust foundation of the GGJT model. Tailored for heightened extensibility and user-centric functionality, GGUF introduces a suite of indispensable features:
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**Single-file Deployment:** Streamline distribution and loading effortlessly. GGUF models have been meticulously architected for seamless deployment, necessitating no external files for supplementary information.
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**Extensibility:** Safeguard the future of your models. GGUF seamlessly accommodates the integration of new features into GGML-based executors, ensuring compatibility with existing models.
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**mmap Compatibility:** Prioritize efficiency. GGUF models are purposefully engineered to support mmap, facilitating rapid loading and saving, thus optimizing your workflow.
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**User-Friendly:** Simplify your coding endeavors. Load and save models effortlessly, irrespective of the programming language used, obviating the dependency on external libraries.
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**Full Information:** A comprehensive repository in a single file. GGUF models encapsulate all requisite information for loading, eliminating the need for users to furnish additional data.
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The differentiator between GGJT and GGUF lies in the deliberate adoption of a key-value structure for hyperparameters (now termed metadata). Bid farewell to untyped lists, and embrace a structured approach that seamlessly accommodates new metadata without compromising compatibility with existing models. Augment your model with supplementary information for enhanced inference and model identification.
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**QUANTIZATION_METHODS:**
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| Method | Quantization | Advantages | Trade-offs |
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|---|---|---|---|
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| q2_k | 2-bit integers | Significant model size reduction | Minimal impact on accuracy |
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| q3_k_l | 3-bit integers | Balance between model size reduction and accuracy preservation | Moderate impact on accuracy |
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| q3_k_m | 3-bit integers | Enhanced accuracy with mixed precision | Increased computational complexity |
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| q3_k_s | 3-bit integers | Improved model efficiency with structured pruning | Reduced accuracy |
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| q4_0 | 4-bit integers | Significant model size reduction | Moderate impact on accuracy |
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| q4_1 | 4-bit integers | Enhanced accuracy with mixed precision | Increased computational complexity |
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| q4_k_m | 4-bit integers | Optimized model size and accuracy with mixed precision and structured pruning | Reduced accuracy |
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| q4_k_s | 4-bit integers | Improved model efficiency with structured pruning | Reduced accuracy |
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| q5_0 | 5-bit integers | Balance between model size reduction and accuracy preservation | Moderate impact on accuracy |
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| q5_1 | 5-bit integers | Enhanced accuracy with mixed precision | Increased computational complexity |
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| q5_k_m | 5-bit integers | Optimized model size and accuracy with mixed precision and structured pruning | Reduced accuracy |
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| q5_k_s | 5-bit integers | Improved model efficiency with structured pruning | Reduced accuracy |
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| q6_k | 6-bit integers | Balance between model size reduction and accuracy preservation | Moderate impact on accuracy |
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| q8_0 | 8-bit integers | Significant model size reduction | Minimal impact on accuracy |
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<div align="center">
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<!-- Replace `#` with your actual links -->
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<a href="https://youtube.com/@devsdocode"><img alt="YouTube" src="https://img.shields.io/badge/YouTube-FF0000?style=for-the-badge&logo=youtube&logoColor=white"></a>
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<a href="https://t.me/devsdocode"><img alt="Telegram" src="https://img.shields.io/badge/Telegram-2CA5E0?style=for-the-badge&logo=telegram&logoColor=white"></a>
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<a href="https://www.instagram.com/sree.shades_/"><img alt="Instagram" src="https://img.shields.io/badge/Instagram-E4405F?style=for-the-badge&logo=instagram&logoColor=white"></a>
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<a href="https://www.linkedin.com/in/developer-sreejan/"><img alt="LinkedIn" src="https://img.shields.io/badge/LinkedIn-0077B5?style=for-the-badge&logo=linkedin&logoColor=white"></a>
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<a href="https://buymeacoffee.com/devsdocode"><img alt="Buy Me A Coffee" src="https://img.shields.io/badge/Buy%20Me%20A%20Coffee-FFDD00?style=for-the-badge&logo=buymeacoffee&logoColor=black"></a>
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</div>
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