Instructions to use WithinUsAI/Gemma3-Prompt.Coder.Uncensored.270m-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WithinUsAI/Gemma3-Prompt.Coder.Uncensored.270m-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("WithinUsAI/Gemma3-Prompt.Coder.Uncensored.270m-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use WithinUsAI/Gemma3-Prompt.Coder.Uncensored.270m-GGUF with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf WithinUsAI/Gemma3-Prompt.Coder.Uncensored.270m-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf WithinUsAI/Gemma3-Prompt.Coder.Uncensored.270m-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf WithinUsAI/Gemma3-Prompt.Coder.Uncensored.270m-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf WithinUsAI/Gemma3-Prompt.Coder.Uncensored.270m-GGUF:Q4_K_M
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf WithinUsAI/Gemma3-Prompt.Coder.Uncensored.270m-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf WithinUsAI/Gemma3-Prompt.Coder.Uncensored.270m-GGUF:Q4_K_M
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf WithinUsAI/Gemma3-Prompt.Coder.Uncensored.270m-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf WithinUsAI/Gemma3-Prompt.Coder.Uncensored.270m-GGUF:Q4_K_M
Use Docker
docker model run hf.co/WithinUsAI/Gemma3-Prompt.Coder.Uncensored.270m-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use WithinUsAI/Gemma3-Prompt.Coder.Uncensored.270m-GGUF with Ollama:
ollama run hf.co/WithinUsAI/Gemma3-Prompt.Coder.Uncensored.270m-GGUF:Q4_K_M
- Unsloth Studio
How to use WithinUsAI/Gemma3-Prompt.Coder.Uncensored.270m-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for WithinUsAI/Gemma3-Prompt.Coder.Uncensored.270m-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for WithinUsAI/Gemma3-Prompt.Coder.Uncensored.270m-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for WithinUsAI/Gemma3-Prompt.Coder.Uncensored.270m-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use WithinUsAI/Gemma3-Prompt.Coder.Uncensored.270m-GGUF with Docker Model Runner:
docker model run hf.co/WithinUsAI/Gemma3-Prompt.Coder.Uncensored.270m-GGUF:Q4_K_M
- Lemonade
How to use WithinUsAI/Gemma3-Prompt.Coder.Uncensored.270m-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull WithinUsAI/Gemma3-Prompt.Coder.Uncensored.270m-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.Gemma3-Prompt.Coder.Uncensored.270m-GGUF-Q4_K_M
List all available models
lemonade list
| base_model: | |
| - google/gemma-3-270m-it | |
| - huihui-ai/Huihui-gemma-3-270m-it-abliterated | |
| - AxionLab-official/DogeAI-v1.5-Coder | |
| - gokaygokay/prompt-enhancer-gemma-3-270m-it | |
| - broadfield-dev/gemma-3-270m-tuned-0106-1020-tuned-0106-1726 | |
| library_name: transformers | |
| tags: | |
| - mergekit | |
| - merge | |
| datasets: | |
| - microsoft/rStar-Coder | |
| - gokaygokay/prompt-enhancement-75k | |
| - gokaygokay/prompt-enhancer-dataset | |
| # Gemma-3-Prompt-Coder-270m-it (Uncensored) | |
| This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit). | |
| ## Merge Details | |
| ### Merge Method | |
| This model was merged using the [SLERP](https://en.wikipedia.org/wiki/Slerp) merge method. | |
| ### Models Merged | |
| The following models were included in the merge: | |
| * huihui-ai-Huihui-gemma-3-270m-it-abliterated | |
| * AxionLab-official-DogeAI-v1.5-Coder | |
| * gokaygokay-prompt-enhancer-gemma-3-270m-it | |
| * broadfield-dev-gemma-3-270m-tuned-0106-1726 | |
| 1. This Is a fine-tuned model based on google/gemma-3-270m-it for enhancing and expanding short prompts into detailed, context-rich descriptions. | |
| 2. This is an uncensored version of google/gemma-3-270m-it, achieved through fine-tuning with the TRL framework. | |
| 3. This model is a fine-tuned version of google/gemma-3-270m-it on the microsoft/rStar-Coder dataset. | |
| ****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. | |
| ``` |