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tensorblock/DaringMaid-20B-GGUF
DaringMaid-20B-GGUF is a text generation model from tensorblock. Use it when you need the model to write or continue text. The card lists the license as cc-by-nc-4.0.
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Downloads · 30 days
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.gguf7.4 GB · 100%
From the Hugging Face model README
This repo contains GGUF format model files for Kooten/DaringMaid-20B.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| DaringMaid-20B-Q2_K.gguf | Q2_K | 6.911 GB | smallest, significant quality loss - not recommended for most purposes |
| DaringMaid-20B-Q3_K_S.gguf | Q3_K_S | 8.064 GB | very small, high quality loss |
| DaringMaid-20B-Q3_K_M.gguf | Q3_K_M | 9.039 GB | very small, high quality loss |
| DaringMaid-20B-Q3_K_L.gguf | Q3_K_L | 9.898 GB | small, substantial quality loss |
| DaringMaid-20B-Q4_0.gguf | Q4_0 | 10.517 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| DaringMaid-20B-Q4_K_S.gguf | Q4_K_S | 10.586 GB | small, greater quality loss |
| DaringMaid-20B-Q4_K_M.gguf | Q4_K_M | 11.215 GB | medium, balanced quality - recommended |
| DaringMaid-20B-Q5_0.gguf | Q5_0 | 12.825 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| DaringMaid-20B-Q5_K_S.gguf | Q5_K_S | 12.825 GB | large, low quality loss - recommended |
| DaringMaid-20B-Q5_K_M.gguf | Q5_K_M | 13.185 GB | large, very low quality loss - recommended |
| DaringMaid-20B-Q6_K.gguf | Q6_K | 15.278 GB | very large, extremely low quality loss |
| DaringMaid-20B-Q8_0.gguf | Q8_0 | 19.787 GB | very large, extremely low quality loss - not recommended |
Firstly, install Huggingface Client
pip install -U "huggingface_hub[cli]"
Then, downoad the individual model file the a local directory
huggingface-cli download tensorblock/DaringMaid-20B-GGUF --include "DaringMaid-20B-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/DaringMaid-20B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'