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AISquare-Instruct-yi-ko-6b-v0.9.26-GGUF
tensorblock/AISquare-Instruct-yi-ko-6b-v0.9.26-GGUF
AISquare-Instruct-yi-ko-6b-v0.9.26-GGUF is a machine learning model from tensorblock. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
<div style="width: auto; margin-left: auto; margin-right: auto" <img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;" </div
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.gguf2.4 GB · 100%
At a glance
- Access
- Public
- Created
- Nov 14, 2024
- Updated
- Jan 27, 2026
- SHA
- 168cf37e
Base models
Model card
From the Hugging Face model README
<div style="width: auto; margin-left: auto; margin-right: auto">
<img src="https://i.imgur.com/jC7kdl8.jpeg" alt="TensorBlock" style="width: 100%; min-width: 400px; display: block; margin: auto;">
</div>
inswave/AISquare-Instruct-yi-ko-6b-v0.9.26 - GGUF
This repo contains GGUF format model files for inswave/AISquare-Instruct-yi-ko-6b-v0.9.26.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.
Our projects
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| Filename | Quant type | File Size | Description |
|---|---|---|---|
| AISquare-Instruct-yi-ko-6b-v0.9.26-Q2_K.gguf | Q2_K | 2.240 GB | smallest, significant quality loss - not recommended for most purposes |
| AISquare-Instruct-yi-ko-6b-v0.9.26-Q3_K_S.gguf | Q3_K_S | 2.592 GB | very small, high quality loss |
| AISquare-Instruct-yi-ko-6b-v0.9.26-Q3_K_M.gguf | Q3_K_M | 2.857 GB | very small, high quality loss |
| AISquare-Instruct-yi-ko-6b-v0.9.26-Q3_K_L.gguf | Q3_K_L | 3.084 GB | small, substantial quality loss |
| AISquare-Instruct-yi-ko-6b-v0.9.26-Q4_0.gguf | Q4_0 | 3.317 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| AISquare-Instruct-yi-ko-6b-v0.9.26-Q4_K_S.gguf | Q4_K_S | 3.339 GB | small, greater quality loss |
| AISquare-Instruct-yi-ko-6b-v0.9.26-Q4_K_M.gguf | Q4_K_M | 3.498 GB | medium, balanced quality - recommended |
| AISquare-Instruct-yi-ko-6b-v0.9.26-Q5_0.gguf | Q5_0 | 3.999 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| AISquare-Instruct-yi-ko-6b-v0.9.26-Q5_K_S.gguf | Q5_K_S | 3.999 GB | large, low quality loss - recommended |
| AISquare-Instruct-yi-ko-6b-v0.9.26-Q5_K_M.gguf | Q5_K_M | 4.092 GB | large, very low quality loss - recommended |
| AISquare-Instruct-yi-ko-6b-v0.9.26-Q6_K.gguf | Q6_K | 4.724 GB | very large, extremely low quality loss |
| AISquare-Instruct-yi-ko-6b-v0.9.26-Q8_0.gguf | Q8_0 | 6.117 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/AISquare-Instruct-yi-ko-6b-v0.9.26-GGUF --include "AISquare-Instruct-yi-ko-6b-v0.9.26-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/AISquare-Instruct-yi-ko-6b-v0.9.26-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
- Created
- Nov 14, 2024
- Updated
- Jan 27, 2026