Nxcode-CQ-7B-orpo-IMat-GGUF
Llama.cpp imatrix quantization of NTQAI/Nxcode-CQ-7B-orpo
Original Model: NTQAI/Nxcode-CQ-7B-orpo
Original dtype: BF16
(bfloat16
)
Quantized by: llama.cpp b3067
IMatrix dataset: here
Files
IMatrix
Status: β
Available
Link: here
Common Quants
All Quants
Downloading using huggingface-cli
If you do not have hugginface-cli installed:
pip install -U "huggingface_hub[cli]"
Download the specific file you want:
huggingface-cli download legraphista/Nxcode-CQ-7B-orpo-IMat-GGUF --include "Nxcode-CQ-7B-orpo.Q8_0.gguf" --local-dir ./
If the model file is big, it has been split into multiple files. In order to download them all to a local folder, run:
huggingface-cli download legraphista/Nxcode-CQ-7B-orpo-IMat-GGUF --include "Nxcode-CQ-7B-orpo.Q8_0/*" --local-dir ./
# see FAQ for merging GGUF's
Inference
Simple chat template
<|im_start|>system
You are a helpful assistant.<|im_end|>
<|im_start|>user
{user_prompt}<|im_end|>
<|im_start|>assistant
{assistant_response}<|im_end|>
<|im_start|>user
{next_user_prompt}<|im_end|>
Chat template with system prompt
<|im_start|>system
{system_prompt}<|im_end|>
<|im_start|>user
{user_prompt}<|im_end|>
<|im_start|>assistant
{assistant_response}<|im_end|>
<|im_start|>user
{next_user_prompt}<|im_end|>
Llama.cpp
llama.cpp/main -m Nxcode-CQ-7B-orpo.Q8_0.gguf --color -i -p "prompt here (according to the chat template)"
FAQ
Why is the IMatrix not applied everywhere?
According to this investigation, it appears that lower quantizations are the only ones that benefit from the imatrix input (as per hellaswag results).
How do I merge a split GGUF?
- Make sure you have
gguf-split
available
- Locate your GGUF chunks folder (ex:
Nxcode-CQ-7B-orpo.Q8_0
)
- Run
gguf-split --merge Nxcode-CQ-7B-orpo.Q8_0/Nxcode-CQ-7B-orpo.Q8_0-00001-of-XXXXX.gguf Nxcode-CQ-7B-orpo.Q8_0.gguf
- Make sure to point
gguf-split
to the first chunk of the split.
Got a suggestion? Ping me @legraphista!