Triangle104/DeepSeek-R1-Distill-Qwen-1.5B-uncensored-Q5_K_S-GGUF

This model was converted to GGUF format from thirdeyeai/DeepSeek-R1-Distill-Qwen-1.5B-uncensored using llama.cpp via the ggml.ai's GGUF-my-repo space. Refer to the original model card for more details on the model.

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Model details:

DeepSeek-R1-Distill-Qwen-1.5B-Uncensored is a text-generation model designed to uphold the values of internet freedom and unrestricted access to information. By offering an uncensored approach, this model enables users to explore ideas, generate content, and engage in discussions without the constraints of over-moderated or filtered outputs. It prioritizes user autonomy and aligns with principles of free speech and open knowledge sharing.

Developed by: Thirdeye AI
Funded by: Thirdeye AI
Shared by: Thirdeye AI
Model type: Distilled Transformer-based Language Model
Language(s) (NLP): English
License: Apache 2.0
Finetuned from model: DeepSeek-R1-Distill-Qwen-1.5B

Model Sources

Repository: DeepSeek-R1-Distill-Qwen-1.5B-Uncensored on Hugging Face
Demo: Available on Hugging Face Hub

Uses Direct Use

The model is intended for applications that demand openness and flexibility in generating creative, exploratory, or critical content. These include:

Free-form writing and storytelling
Open-ended discussions
Exploratory content generation for sensitive or nuanced topics

Downstream Use

Users can fine-tune this model for specialized domains where censorship-free text generation is required, such as:

Journalism and investigative research
Creative projects that push artistic boundaries
Academic applications exploring controversial or complex topics

Out-of-Scope Use

This model should not be used for harmful, illegal, or unethical activities. Users must comply with applicable laws and ensure that the model's outputs do not infringe on others' rights. Bias, Risks, and Limitations Risks

While the uncensored approach promotes freedom, it may produce outputs that are controversial, offensive, or factually inaccurate. Users must exercise discretion when interpreting the model's outputs and take responsibility for their use. Recommendations

Use responsibly, especially in contexts where outputs could impact individuals or communities.
Employ content moderation or review processes for high-stakes applications.

The Case for Uncensored Models

Thirdeye AI believes in the transformative power of open models that respect user autonomy and internet freedom. In a world where over-moderation can stifle innovation and critical thought, uncensored models empower individuals to explore and create without artificial constraints. This aligns with our mission to advance free and open access to AI tools.

By releasing this model, we aim to support the following:

Freedom of Expression: Unrestricted AI tools enable users to articulate diverse perspectives and engage in meaningful conversations.
Transparency and Trust: Users deserve access to tools that operate openly, fostering accountability and understanding of AI behaviors.
Creative Empowerment: The absence of censorship allows for boundary-pushing content creation that might otherwise be suppressed.

How to Get Started with the Model

from transformers import pipeline

generator = pipeline("text-generation", model="thirdeyeai/DeepSeek-R1-Distill-Qwen-1.5B-uncensored") response = generator("The importance of free speech is") print(response)

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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 Triangle104/DeepSeek-R1-Distill-Qwen-1.5B-uncensored-Q5_K_S-GGUF --hf-file deepseek-r1-distill-qwen-1.5b-uncensored-q5_k_s.gguf -p "The meaning to life and the universe is"

Server:

llama-server --hf-repo Triangle104/DeepSeek-R1-Distill-Qwen-1.5B-uncensored-Q5_K_S-GGUF --hf-file deepseek-r1-distill-qwen-1.5b-uncensored-q5_k_s.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 Triangle104/DeepSeek-R1-Distill-Qwen-1.5B-uncensored-Q5_K_S-GGUF --hf-file deepseek-r1-distill-qwen-1.5b-uncensored-q5_k_s.gguf -p "The meaning to life and the universe is"

or

./llama-server --hf-repo Triangle104/DeepSeek-R1-Distill-Qwen-1.5B-uncensored-Q5_K_S-GGUF --hf-file deepseek-r1-distill-qwen-1.5b-uncensored-q5_k_s.gguf -c 2048