metadata
license: apache-2.0
datasets:
- tatsu-lab/alpaca
language:
- en
base_model: LordNoah/Alpaca-tuned-gpt2
tags:
- TensorBlock
- GGUF
LordNoah/Alpaca-tuned-gpt2 - GGUF
This repo contains GGUF format model files for LordNoah/Alpaca-tuned-gpt2.
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 |
|---|---|---|---|
| Alpaca-tuned-gpt2-Q2_K.gguf | Q2_K | 0.346 GB | smallest, significant quality loss - not recommended for most purposes |
| Alpaca-tuned-gpt2-Q3_K_S.gguf | Q3_K_S | 0.394 GB | very small, high quality loss |
| Alpaca-tuned-gpt2-Q3_K_M.gguf | Q3_K_M | 0.458 GB | very small, high quality loss |
| Alpaca-tuned-gpt2-Q3_K_L.gguf | Q3_K_L | 0.494 GB | small, substantial quality loss |
| Alpaca-tuned-gpt2-Q4_0.gguf | Q4_0 | 0.497 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| Alpaca-tuned-gpt2-Q4_K_S.gguf | Q4_K_S | 0.500 GB | small, greater quality loss |
| Alpaca-tuned-gpt2-Q4_K_M.gguf | Q4_K_M | 0.549 GB | medium, balanced quality - recommended |
| Alpaca-tuned-gpt2-Q5_0.gguf | Q5_0 | 0.593 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| Alpaca-tuned-gpt2-Q5_K_S.gguf | Q5_K_S | 0.593 GB | large, low quality loss - recommended |
| Alpaca-tuned-gpt2-Q5_K_M.gguf | Q5_K_M | 0.632 GB | large, very low quality loss - recommended |
| Alpaca-tuned-gpt2-Q6_K.gguf | Q6_K | 0.696 GB | very large, extremely low quality loss |
| Alpaca-tuned-gpt2-Q8_0.gguf | Q8_0 | 0.898 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/Alpaca-tuned-gpt2-GGUF --include "Alpaca-tuned-gpt2-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/Alpaca-tuned-gpt2-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'