metadata
license: apache-2.0
language:
- en
- zh
base_model: prithivMLmods/Ophiuchi-Qwen3-14B-Instruct
pipeline_tag: text-generation
library_name: transformers
tags:
- text-generation-inference
- code
- math
- moe
- TensorBlock
- GGUF
datasets:
- open-r1/OpenR1-Math-220k
- deepmind/math_dataset
- burtenshaw/tulu-3-sft-personas-code-no-prompt
prithivMLmods/Ophiuchi-Qwen3-14B-Instruct - GGUF
This repo contains GGUF format model files for prithivMLmods/Ophiuchi-Qwen3-14B-Instruct.
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 |
|---|---|---|---|
| Ophiuchi-Qwen3-14B-Instruct-Q2_K.gguf | Q2_K | 5.754 GB | smallest, significant quality loss - not recommended for most purposes |
| Ophiuchi-Qwen3-14B-Instruct-Q3_K_S.gguf | Q3_K_S | 6.657 GB | very small, high quality loss |
| Ophiuchi-Qwen3-14B-Instruct-Q3_K_M.gguf | Q3_K_M | 7.321 GB | very small, high quality loss |
| Ophiuchi-Qwen3-14B-Instruct-Q3_K_L.gguf | Q3_K_L | 7.901 GB | small, substantial quality loss |
| Ophiuchi-Qwen3-14B-Instruct-Q4_0.gguf | Q4_0 | 8.515 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| Ophiuchi-Qwen3-14B-Instruct-Q4_K_S.gguf | Q4_K_S | 8.573 GB | small, greater quality loss |
| Ophiuchi-Qwen3-14B-Instruct-Q4_K_M.gguf | Q4_K_M | 9.002 GB | medium, balanced quality - recommended |
| Ophiuchi-Qwen3-14B-Instruct-Q5_0.gguf | Q5_0 | 10.264 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| Ophiuchi-Qwen3-14B-Instruct-Q5_K_S.gguf | Q5_K_S | 10.264 GB | large, low quality loss - recommended |
| Ophiuchi-Qwen3-14B-Instruct-Q5_K_M.gguf | Q5_K_M | 10.515 GB | large, very low quality loss - recommended |
| Ophiuchi-Qwen3-14B-Instruct-Q6_K.gguf | Q6_K | 12.122 GB | very large, extremely low quality loss |
| Ophiuchi-Qwen3-14B-Instruct-Q8_0.gguf | Q8_0 | 15.699 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/prithivMLmods_Ophiuchi-Qwen3-14B-Instruct-GGUF --include "Ophiuchi-Qwen3-14B-Instruct-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/prithivMLmods_Ophiuchi-Qwen3-14B-Instruct-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'