Update README.md

README.md

@@ -1,9 +1,8 @@
 ---
-language:
-- en
-license: apache-2.0
 library_name: transformers
 tags:
+- llama-cpp
+- gguf-my-repo
 - uncensored
 - transformers
 - llama
@@ -11,35 +10,66 @@ tags:
 - unsloth
 - llama-cpp
 - gguf-my-repo
+language:
+- en
+license: apache-2.0
 pipeline_tag: text-generation
 ---
 
-# DevsDoCode/LLama-3-8b-Uncensored-Q4_0-GGUF
-This model was converted to GGUF format from [`DevsDoCode/LLama-3-8b-Uncensored`](https://huggingface.co/DevsDoCode/LLama-3-8b-Uncensored) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
-Refer to the [original model card](https://huggingface.co/DevsDoCode/LLama-3-8b-Uncensored) for more details on the model.
-## Use with llama.cpp
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+
+## Crafted with ❤️ by Devs Do Code (Sree)
+
+### GGUF Technical Specifications 
+
+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:
+
+**Single-file Deployment:** Streamline distribution and loading effortlessly. GGUF models have been meticulously architected for seamless deployment, necessitating no external files for supplementary information.
+
+**Extensibility:** Safeguard the future of your models. GGUF seamlessly accommodates the integration of new features into GGML-based executors, ensuring compatibility with existing models.
+
+**mmap Compatibility:** Prioritize efficiency. GGUF models are purposefully engineered to support mmap, facilitating rapid loading and saving, thus optimizing your workflow.
+
+**User-Friendly:** Simplify your coding endeavors. Load and save models effortlessly, irrespective of the programming language used, obviating the dependency on external libraries.
 
-Install llama.cpp through brew.
+**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.
 
-```bash
-brew install ggerganov/ggerganov/llama.cpp
-```
-Invoke the llama.cpp server or the CLI.
+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.
 
-CLI:
 
-```bash
-llama-cli --hf-repo DevsDoCode/LLama-3-8b-Uncensored-Q4_0-GGUF --model llama-3-8b-uncensored.Q4_0.gguf -p "The meaning to life and the universe is"
-```
+**QUANTIZATION_METHODS:**
 
-Server:
+| Method | Quantization | Advantages | Trade-offs |
+|---|---|---|---|
+| q2_k | 2-bit integers | Significant model size reduction | Minimal impact on accuracy |
+| q3_k_l | 3-bit integers | Balance between model size reduction and accuracy preservation | Moderate impact on accuracy |
+| q3_k_m | 3-bit integers | Enhanced accuracy with mixed precision | Increased computational complexity |
+| q3_k_s | 3-bit integers | Improved model efficiency with structured pruning | Reduced accuracy |
+| q4_0 | 4-bit integers | Significant model size reduction | Moderate impact on accuracy |
+| q4_1 | 4-bit integers | Enhanced accuracy with mixed precision | Increased computational complexity |
+| q4_k_m | 4-bit integers | Optimized model size and accuracy with mixed precision and structured pruning | Reduced accuracy |
+| q4_k_s | 4-bit integers | Improved model efficiency with structured pruning | Reduced accuracy |
+| q5_0 | 5-bit integers | Balance between model size reduction and accuracy preservation | Moderate impact on accuracy |
+| q5_1 | 5-bit integers | Enhanced accuracy with mixed precision | Increased computational complexity |
+| q5_k_m | 5-bit integers | Optimized model size and accuracy with mixed precision and structured pruning | Reduced accuracy |
+| q5_k_s | 5-bit integers | Improved model efficiency with structured pruning | Reduced accuracy |
+| q6_k | 6-bit integers | Balance between model size reduction and accuracy preservation | Moderate impact on accuracy |
+| q8_0 | 8-bit integers | Significant model size reduction | Minimal impact on accuracy |
 
-```bash
-llama-server --hf-repo DevsDoCode/LLama-3-8b-Uncensored-Q4_0-GGUF --model llama-3-8b-uncensored.Q4_0.gguf -c 2048
-```
 
-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.
 
-```
-git clone https://github.com/ggerganov/llama.cpp &&             cd llama.cpp &&             make &&             ./main -m llama-3-8b-uncensored.Q4_0.gguf -n 128
-```
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