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tensorblock/dotvignesh_perry-7b-GGUF
dotvignesh_perry-7b-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.
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Downloads · 30 days
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.gguf2.5 GB · 100%
From the Hugging Face model README
This repo contains GGUF format model files for dotvignesh/perry-7b.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b5165.
Unable to determine prompt format automatically. Please check the original model repository for the correct prompt format.
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| perry-7b-Q2_K.gguf | Q2_K | 2.533 GB | smallest, significant quality loss - not recommended for most purposes |
| perry-7b-Q3_K_S.gguf | Q3_K_S | 2.948 GB | very small, high quality loss |
| perry-7b-Q3_K_M.gguf | Q3_K_M | 3.298 GB | very small, high quality loss |
| perry-7b-Q3_K_L.gguf | Q3_K_L | 3.597 GB | small, substantial quality loss |
| perry-7b-Q4_0.gguf | Q4_0 | 3.826 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| perry-7b-Q4_K_S.gguf | Q4_K_S | 3.857 GB | small, greater quality loss |
| perry-7b-Q4_K_M.gguf | Q4_K_M | 4.081 GB | medium, balanced quality - recommended |
| perry-7b-Q5_0.gguf | Q5_0 | 4.652 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| perry-7b-Q5_K_S.gguf | Q5_K_S | 4.652 GB | large, low quality loss - recommended |
| perry-7b-Q5_K_M.gguf | Q5_K_M | 4.783 GB | large, very low quality loss - recommended |
| perry-7b-Q6_K.gguf | Q6_K | 5.529 GB | very large, extremely low quality loss |
| perry-7b-Q8_0.gguf | Q8_0 | 7.161 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/dotvignesh_perry-7b-GGUF --include "perry-7b-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/dotvignesh_perry-7b-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'