Feedback and support: TensorBlock's Twitter/X, Telegram Group and Discord server
acrastt/OmegLLaMA-3B - GGUF
This repo contains GGUF format model files for acrastt/OmegLLaMA-3B.
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 |
---|---|---|---|
OmegLLaMA-3B-Q2_K.gguf | Q2_K | 1.844 GB | smallest, significant quality loss - not recommended for most purposes |
OmegLLaMA-3B-Q3_K_S.gguf | Q3_K_S | 1.844 GB | very small, high quality loss |
OmegLLaMA-3B-Q3_K_M.gguf | Q3_K_M | 1.992 GB | very small, high quality loss |
OmegLLaMA-3B-Q3_K_L.gguf | Q3_K_L | 2.062 GB | small, substantial quality loss |
OmegLLaMA-3B-Q4_0.gguf | Q4_0 | 1.844 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
OmegLLaMA-3B-Q4_K_S.gguf | Q4_K_S | 2.238 GB | small, greater quality loss |
OmegLLaMA-3B-Q4_K_M.gguf | Q4_K_M | 2.403 GB | medium, balanced quality - recommended |
OmegLLaMA-3B-Q5_0.gguf | Q5_0 | 2.231 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
OmegLLaMA-3B-Q5_K_S.gguf | Q5_K_S | 2.424 GB | large, low quality loss - recommended |
OmegLLaMA-3B-Q5_K_M.gguf | Q5_K_M | 2.568 GB | large, very low quality loss - recommended |
OmegLLaMA-3B-Q6_K.gguf | Q6_K | 3.392 GB | very large, extremely low quality loss |
OmegLLaMA-3B-Q8_0.gguf | Q8_0 | 3.392 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/OmegLLaMA-3B-GGUF --include "OmegLLaMA-3B-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/OmegLLaMA-3B-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
- Downloads last month
- 158
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Model tree for tensorblock/OmegLLaMA-3B-GGUF
Base model
acrastt/OmegLLaMA-3BDataset used to train tensorblock/OmegLLaMA-3B-GGUF
Evaluation results
- normalized accuracy on AI2 Reasoning Challenge (25-Shot)test set Open LLM Leaderboard40.360
- normalized accuracy on HellaSwag (10-Shot)validation set Open LLM Leaderboard66.130
- accuracy on MMLU (5-Shot)test set Open LLM Leaderboard28.000
- mc2 on TruthfulQA (0-shot)validation set Open LLM Leaderboard33.310
- accuracy on Winogrande (5-shot)validation set Open LLM Leaderboard61.640
- accuracy on GSM8k (5-shot)test set Open LLM Leaderboard0.230