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hyper-accel/tiny-random-olmo - GGUF
This repo contains GGUF format model files for hyper-accel/tiny-random-olmo.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4882.
Prompt template
Unable to determine prompt format automatically. Please check the original model repository for the correct prompt format.
Model file specification
Filename | Quant type | File Size | Description |
---|---|---|---|
tiny-random-olmo-Q2_K.gguf | Q2_K | 0.034 GB | smallest, significant quality loss - not recommended for most purposes |
tiny-random-olmo-Q3_K_S.gguf | Q3_K_S | 0.037 GB | very small, high quality loss |
tiny-random-olmo-Q3_K_M.gguf | Q3_K_M | 0.037 GB | very small, high quality loss |
tiny-random-olmo-Q3_K_L.gguf | Q3_K_L | 0.037 GB | small, substantial quality loss |
tiny-random-olmo-Q4_0.gguf | Q4_0 | 0.041 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
tiny-random-olmo-Q4_K_S.gguf | Q4_K_S | 0.041 GB | small, greater quality loss |
tiny-random-olmo-Q4_K_M.gguf | Q4_K_M | 0.041 GB | medium, balanced quality - recommended |
tiny-random-olmo-Q5_0.gguf | Q5_0 | 0.045 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
tiny-random-olmo-Q5_K_S.gguf | Q5_K_S | 0.045 GB | large, low quality loss - recommended |
tiny-random-olmo-Q5_K_M.gguf | Q5_K_M | 0.045 GB | large, very low quality loss - recommended |
tiny-random-olmo-Q6_K.gguf | Q6_K | 0.050 GB | very large, extremely low quality loss |
tiny-random-olmo-Q8_0.gguf | Q8_0 | 0.063 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/tiny-random-olmo-GGUF --include "tiny-random-olmo-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/tiny-random-olmo-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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Model tree for tensorblock/tiny-random-olmo-GGUF
Base model
hyper-accel/tiny-random-olmo