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Locutusque/Orca-2-13b-SFT-v6 - GGUF
This repo contains GGUF format model files for Locutusque/Orca-2-13b-SFT-v6.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.
Prompt template
Model file specification
Filename | Quant type | File Size | Description |
---|---|---|---|
Orca-2-13b-SFT-v6-Q2_K.gguf | Q2_K | 4.521 GB | smallest, significant quality loss - not recommended for most purposes |
Orca-2-13b-SFT-v6-Q3_K_S.gguf | Q3_K_S | 5.270 GB | very small, high quality loss |
Orca-2-13b-SFT-v6-Q3_K_M.gguf | Q3_K_M | 5.903 GB | very small, high quality loss |
Orca-2-13b-SFT-v6-Q3_K_L.gguf | Q3_K_L | 6.454 GB | small, substantial quality loss |
Orca-2-13b-SFT-v6-Q4_0.gguf | Q4_0 | 6.860 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
Orca-2-13b-SFT-v6-Q4_K_S.gguf | Q4_K_S | 6.913 GB | small, greater quality loss |
Orca-2-13b-SFT-v6-Q4_K_M.gguf | Q4_K_M | 7.326 GB | medium, balanced quality - recommended |
Orca-2-13b-SFT-v6-Q5_0.gguf | Q5_0 | 8.356 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
Orca-2-13b-SFT-v6-Q5_K_S.gguf | Q5_K_S | 8.356 GB | large, low quality loss - recommended |
Orca-2-13b-SFT-v6-Q5_K_M.gguf | Q5_K_M | 8.596 GB | large, very low quality loss - recommended |
Orca-2-13b-SFT-v6-Q6_K.gguf | Q6_K | 9.946 GB | very large, extremely low quality loss |
Orca-2-13b-SFT-v6-Q8_0.gguf | Q8_0 | 12.881 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/Orca-2-13b-SFT-v6-GGUF --include "Orca-2-13b-SFT-v6-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/Orca-2-13b-SFT-v6-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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Model tree for tensorblock/Orca-2-13b-SFT-v6-GGUF
Datasets used to train tensorblock/Orca-2-13b-SFT-v6-GGUF
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard60.410
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard80.460
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard59.510
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard54.010
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard77.430
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard5.080