metadata
library_name: transformers
tags:
- TensorBlock
- GGUF
base_model: Jayamurugan/Ikig-AI
Jayamurugan/Ikig-AI - GGUF
This repo contains GGUF format model files for Jayamurugan/Ikig-AI.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.
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Model file specification
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| Ikig-AI-Q2_K.gguf | Q2_K | 2.337 GB | smallest, significant quality loss - not recommended for most purposes |
| Ikig-AI-Q3_K_S.gguf | Q3_K_S | 2.709 GB | very small, high quality loss |
| Ikig-AI-Q3_K_M.gguf | Q3_K_M | 2.993 GB | very small, high quality loss |
| Ikig-AI-Q3_K_L.gguf | Q3_K_L | 3.237 GB | small, substantial quality loss |
| Ikig-AI-Q4_0.gguf | Q4_0 | 3.479 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| Ikig-AI-Q4_K_S.gguf | Q4_K_S | 3.503 GB | small, greater quality loss |
| Ikig-AI-Q4_K_M.gguf | Q4_K_M | 3.674 GB | medium, balanced quality - recommended |
| Ikig-AI-Q5_0.gguf | Q5_0 | 4.204 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| Ikig-AI-Q5_K_S.gguf | Q5_K_S | 4.204 GB | large, low quality loss - recommended |
| Ikig-AI-Q5_K_M.gguf | Q5_K_M | 4.304 GB | large, very low quality loss - recommended |
| Ikig-AI-Q6_K.gguf | Q6_K | 4.974 GB | very large, extremely low quality loss |
| Ikig-AI-Q8_0.gguf | Q8_0 | 6.442 GB | very large, extremely low quality loss - not recommended |
Downloading instruction
Command line
Firstly, install Huggingface Client
pip install -U "huggingface_hub[cli]"
Then, downoad the individual model file the a local directory
huggingface-cli download tensorblock/Ikig-AI-GGUF --include "Ikig-AI-Q2_K.gguf" --local-dir MY_LOCAL_DIR
If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf), you can try:
huggingface-cli download tensorblock/Ikig-AI-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'