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tensorblock/
duchao1210_qwen_2.5_sft_1k_r16-GGUF

Name: duchao1210_qwen_2.5_sft_1k_r16-GGUF
Availability: InStock

duchao1210/qwen_2.5_sft_1k_r16

text-generation-inference

transformers

trl

unsloth

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duchao1210/qwen_2.5_sft_1k_r16 - GGUF

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This repo contains GGUF format model files for duchao1210/qwen_2.5_sft_1k_r16.

The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b5753.

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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
qwen_2.5_sft_1k_r16-Q2_K.gguf	Q2_K	1.275 GB	smallest, significant quality loss - not recommended for most purposes
qwen_2.5_sft_1k_r16-Q3_K_S.gguf	Q3_K_S	1.454 GB	very small, high quality loss
qwen_2.5_sft_1k_r16-Q3_K_M.gguf	Q3_K_M	1.590 GB	very small, high quality loss
qwen_2.5_sft_1k_r16-Q3_K_L.gguf	Q3_K_L	1.707 GB	small, substantial quality loss
qwen_2.5_sft_1k_r16-Q4_0.gguf	Q4_0	1.823 GB	legacy; small, very high quality loss - prefer using Q3_K_M
qwen_2.5_sft_1k_r16-Q4_K_S.gguf	Q4_K_S	1.834 GB	small, greater quality loss
qwen_2.5_sft_1k_r16-Q4_K_M.gguf	Q4_K_M	1.930 GB	medium, balanced quality - recommended
qwen_2.5_sft_1k_r16-Q5_0.gguf	Q5_0	2.170 GB	legacy; medium, balanced quality - prefer using Q4_K_M
qwen_2.5_sft_1k_r16-Q5_K_S.gguf	Q5_K_S	2.170 GB	large, low quality loss - recommended
qwen_2.5_sft_1k_r16-Q5_K_M.gguf	Q5_K_M	2.225 GB	large, very low quality loss - recommended
qwen_2.5_sft_1k_r16-Q6_K.gguf	Q6_K	2.538 GB	very large, extremely low quality loss
qwen_2.5_sft_1k_r16-Q8_0.gguf	Q8_0	3.285 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/duchao1210_qwen_2.5_sft_1k_r16-GGUF --include "qwen_2.5_sft_1k_r16-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/duchao1210_qwen_2.5_sft_1k_r16-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'