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fblgit/cybertron-v4-qw7B-MGS - GGUF
This repo contains GGUF format model files for fblgit/cybertron-v4-qw7B-MGS.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.
Prompt template
<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
Model file specification
Filename | Quant type | File Size | Description |
---|---|---|---|
cybertron-v4-qw7B-MGS-Q2_K.gguf | Q2_K | 3.016 GB | smallest, significant quality loss - not recommended for most purposes |
cybertron-v4-qw7B-MGS-Q3_K_S.gguf | Q3_K_S | 3.492 GB | very small, high quality loss |
cybertron-v4-qw7B-MGS-Q3_K_M.gguf | Q3_K_M | 3.808 GB | very small, high quality loss |
cybertron-v4-qw7B-MGS-Q3_K_L.gguf | Q3_K_L | 4.088 GB | small, substantial quality loss |
cybertron-v4-qw7B-MGS-Q4_0.gguf | Q4_0 | 4.431 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
cybertron-v4-qw7B-MGS-Q4_K_S.gguf | Q4_K_S | 4.458 GB | small, greater quality loss |
cybertron-v4-qw7B-MGS-Q4_K_M.gguf | Q4_K_M | 4.683 GB | medium, balanced quality - recommended |
cybertron-v4-qw7B-MGS-Q5_0.gguf | Q5_0 | 5.315 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
cybertron-v4-qw7B-MGS-Q5_K_S.gguf | Q5_K_S | 5.315 GB | large, low quality loss - recommended |
cybertron-v4-qw7B-MGS-Q5_K_M.gguf | Q5_K_M | 5.445 GB | large, very low quality loss - recommended |
cybertron-v4-qw7B-MGS-Q6_K.gguf | Q6_K | 6.254 GB | very large, extremely low quality loss |
cybertron-v4-qw7B-MGS-Q8_0.gguf | Q8_0 | 8.099 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/cybertron-v4-qw7B-MGS-GGUF --include "cybertron-v4-qw7B-MGS-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/cybertron-v4-qw7B-MGS-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
- Downloads last month
- 320
Model tree for tensorblock/cybertron-v4-qw7B-MGS-GGUF
Base model
Qwen/Qwen2.5-7B
Finetuned
Qwen/Qwen2.5-7B-Instruct
Finetuned
fblgit/cybertron-v4-qw7B-MGS
Dataset used to train tensorblock/cybertron-v4-qw7B-MGS-GGUF
Evaluation results
- strict accuracy on IFEval (0-Shot)Open LLM Leaderboard62.640
- normalized accuracy on BBH (3-Shot)Open LLM Leaderboard37.040
- exact match on MATH Lvl 5 (4-Shot)Open LLM Leaderboard27.720
- acc_norm on GPQA (0-shot)Open LLM Leaderboard8.050
- acc_norm on MuSR (0-shot)Open LLM Leaderboard13.200
- accuracy on MMLU-PRO (5-shot)test set Open LLM Leaderboard38.590