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abacusai/MetaMath-bagel-34b-v0.2-c1500 - GGUF
This repo contains GGUF format model files for abacusai/MetaMath-bagel-34b-v0.2-c1500.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4242.
Prompt template
[INST] <<SYS>>
{system_prompt}
<</SYS>>
{prompt} [/INST]
Model file specification
Filename | Quant type | File Size | Description |
---|---|---|---|
MetaMath-bagel-34b-v0.2-c1500-Q2_K.gguf | Q2_K | 12.825 GB | smallest, significant quality loss - not recommended for most purposes |
MetaMath-bagel-34b-v0.2-c1500-Q3_K_S.gguf | Q3_K_S | 14.960 GB | very small, high quality loss |
MetaMath-bagel-34b-v0.2-c1500-Q3_K_M.gguf | Q3_K_M | 16.655 GB | very small, high quality loss |
MetaMath-bagel-34b-v0.2-c1500-Q3_K_L.gguf | Q3_K_L | 18.139 GB | small, substantial quality loss |
MetaMath-bagel-34b-v0.2-c1500-Q4_0.gguf | Q4_0 | 19.467 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
MetaMath-bagel-34b-v0.2-c1500-Q4_K_S.gguf | Q4_K_S | 19.599 GB | small, greater quality loss |
MetaMath-bagel-34b-v0.2-c1500-Q4_K_M.gguf | Q4_K_M | 20.659 GB | medium, balanced quality - recommended |
MetaMath-bagel-34b-v0.2-c1500-Q5_0.gguf | Q5_0 | 23.708 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
MetaMath-bagel-34b-v0.2-c1500-Q5_K_S.gguf | Q5_K_S | 23.708 GB | large, low quality loss - recommended |
MetaMath-bagel-34b-v0.2-c1500-Q5_K_M.gguf | Q5_K_M | 24.322 GB | large, very low quality loss - recommended |
MetaMath-bagel-34b-v0.2-c1500-Q6_K.gguf | Q6_K | 28.214 GB | very large, extremely low quality loss |
MetaMath-bagel-34b-v0.2-c1500-Q8_0.gguf | Q8_0 | 36.542 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/MetaMath-bagel-34b-v0.2-c1500-GGUF --include "MetaMath-bagel-34b-v0.2-c1500-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/MetaMath-bagel-34b-v0.2-c1500-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
- Downloads last month
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Model tree for tensorblock/MetaMath-bagel-34b-v0.2-c1500-GGUF
Base model
abacusai/MetaMath-bagel-34b-v0.2-c1500