base_model: huihui-ai/Phi-4-mini-reasoning-abliterated
language:

• en
  library_name: transformers
  license: mit
  license_link: https://huggingface.co/huihui-ai/Phi-4-mini-reasoning-abliterated/resolve/main/LICENSE
  pipeline_tag: text-generation
  tags:

• nlp

• math

• code

• chat

• abliterated

• uncensored

• llama-cpp

• gguf-my-repo
  widget:

• messages:

  • role: user
    content: How to solve 3x^2+4x+5=1?
    extra_gated_prompt: 'Usage Warnings

  “Risk of Sensitive or Controversial Outputs“: This model’s safety filtering
  has been significantly reduced, potentially generating sensitive, controversial,
  or inappropriate content. Users should exercise caution and rigorously review generated
  outputs.

  “Not Suitable for All Audiences:“ Due to limited content filtering, the model’s
  outputs may be inappropriate for public settings, underage users, or applications
  requiring high security.

  “Legal and Ethical Responsibilities“: Users must ensure their usage complies
  with local laws and ethical standards. Generated content may carry legal or ethical
  risks, and users are solely responsible for any consequences.

  “Research and Experimental Use“: It is recommended to use this model for research,
  testing, or controlled environments, avoiding direct use in production or public-facing
  commercial applications.

  “Monitoring and Review Recommendations“: Users are strongly advised to monitor
  model outputs in real-time and conduct manual reviews when necessary to prevent
  the dissemination of inappropriate content.

  “No Default Safety Guarantees“: Unlike standard models, this model has not undergone
  rigorous safety optimization. huihui.ai bears no responsibility for any consequences
  arising from its use.'

ldostadi/Phi-4-mini-reasoning-abliterated-Q4_K_M-GGUF

This model was converted to GGUF format from huihui-ai/Phi-4-mini-reasoning-abliterated using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.

Use with llama.cpp

Install llama.cpp through brew (works on Mac and Linux)

brew install llama.cpp

Invoke the llama.cpp server or the CLI.

CLI:

llama-cli --hf-repo ldostadi/Phi-4-mini-reasoning-abliterated-Q4_K_M-GGUF --hf-file phi-4-mini-reasoning-abliterated-q4_k_m.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo ldostadi/Phi-4-mini-reasoning-abliterated-Q4_K_M-GGUF --hf-file phi-4-mini-reasoning-abliterated-q4_k_m.gguf -c 2048

Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.

Step 1: Clone llama.cpp from GitHub.

git clone https://github.com/ggerganov/llama.cpp

Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).

cd llama.cpp && LLAMA_CURL=1 make

Step 3: Run inference through the main binary.

./llama-cli --hf-repo ldostadi/Phi-4-mini-reasoning-abliterated-Q4_K_M-GGUF --hf-file phi-4-mini-reasoning-abliterated-q4_k_m.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo ldostadi/Phi-4-mini-reasoning-abliterated-Q4_K_M-GGUF --hf-file phi-4-mini-reasoning-abliterated-q4_k_m.gguf -c 2048