license: mit
license_link: https://huggingface.co/huihui-ai/Phi-4-mini-instruct-abliterated/resolve/main/LICENSE
language:
- multilingual
- ar
- zh
- cs
- da
- nl
- en
- fi
- fr
- de
- he
- hu
- it
- ja
- ko
- 'no'
- pl
- pt
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- sv
- th
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- uk
pipeline_tag: text-generation
base_model: huihui-ai/Phi-4-mini-instruct-abliterated
tags: - nlp
- code
- abliterated
- uncensored
- TensorBlock
- GGUF
widget: - messages:
- role: user
content: Can you provide ways to eat combinations of bananas and dragonfruits?
library_name: transformers
- role: user
huihui-ai/Phi-4-mini-instruct-abliterated - GGUF
This repo contains GGUF format model files for huihui-ai/Phi-4-mini-instruct-abliterated.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4882.
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Model file specification
| Filename | Quant type | File Size | Description |
|---|---|---|---|
| Phi-4-mini-instruct-abliterated-Q2_K.gguf | Q2_K | 1.683 GB | smallest, significant quality loss - not recommended for most purposes |
| Phi-4-mini-instruct-abliterated-Q3_K_S.gguf | Q3_K_S | 1.897 GB | very small, high quality loss |
| Phi-4-mini-instruct-abliterated-Q3_K_M.gguf | Q3_K_M | 2.118 GB | very small, high quality loss |
| Phi-4-mini-instruct-abliterated-Q3_K_L.gguf | Q3_K_L | 2.250 GB | small, substantial quality loss |
| Phi-4-mini-instruct-abliterated-Q4_0.gguf | Q4_0 | 2.325 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
| Phi-4-mini-instruct-abliterated-Q4_K_S.gguf | Q4_K_S | 2.338 GB | small, greater quality loss |
| Phi-4-mini-instruct-abliterated-Q4_K_M.gguf | Q4_K_M | 2.492 GB | medium, balanced quality - recommended |
| Phi-4-mini-instruct-abliterated-Q5_0.gguf | Q5_0 | 2.728 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
| Phi-4-mini-instruct-abliterated-Q5_K_S.gguf | Q5_K_S | 2.728 GB | large, low quality loss - recommended |
| Phi-4-mini-instruct-abliterated-Q5_K_M.gguf | Q5_K_M | 2.848 GB | large, very low quality loss - recommended |
| Phi-4-mini-instruct-abliterated-Q6_K.gguf | Q6_K | 3.156 GB | very large, extremely low quality loss |
| Phi-4-mini-instruct-abliterated-Q8_0.gguf | Q8_0 | 4.085 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/Phi-4-mini-instruct-abliterated-GGUF --include "Phi-4-mini-instruct-abliterated-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/Phi-4-mini-instruct-abliterated-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'