GGUF
English
text-detoxification
text2text-generation
detoxification
content-moderation
toxicity-reduction
llama
minibase
medium-model
4096-context
Eval Results (legacy)
Instructions to use Minibase/Detoxify-Language-Medium with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use Minibase/Detoxify-Language-Medium with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="Minibase/Detoxify-Language-Medium", filename="detoxify-medium-q8_0.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use Minibase/Detoxify-Language-Medium with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Minibase/Detoxify-Language-Medium:Q8_0 # Run inference directly in the terminal: llama-cli -hf Minibase/Detoxify-Language-Medium:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf Minibase/Detoxify-Language-Medium:Q8_0 # Run inference directly in the terminal: llama-cli -hf Minibase/Detoxify-Language-Medium:Q8_0
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 Minibase/Detoxify-Language-Medium:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf Minibase/Detoxify-Language-Medium:Q8_0
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 Minibase/Detoxify-Language-Medium:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf Minibase/Detoxify-Language-Medium:Q8_0
Use Docker
docker model run hf.co/Minibase/Detoxify-Language-Medium:Q8_0
- LM Studio
- Jan
- Ollama
How to use Minibase/Detoxify-Language-Medium with Ollama:
ollama run hf.co/Minibase/Detoxify-Language-Medium:Q8_0
- Unsloth Studio
How to use Minibase/Detoxify-Language-Medium 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 Minibase/Detoxify-Language-Medium 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 Minibase/Detoxify-Language-Medium to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Minibase/Detoxify-Language-Medium to start chatting
- Docker Model Runner
How to use Minibase/Detoxify-Language-Medium with Docker Model Runner:
docker model run hf.co/Minibase/Detoxify-Language-Medium:Q8_0
- Lemonade
How to use Minibase/Detoxify-Language-Medium with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Minibase/Detoxify-Language-Medium:Q8_0
Run and chat with the model
lemonade run user.Detoxify-Language-Medium-Q8_0
List all available models
lemonade list
| ================================================================================ | |
| DETOXIFY-MEDIUM MODEL BENCHMARK RESULTS | |
| ================================================================================ | |
| π EXECUTIVE SUMMARY | |
| -------------------------------------------------- | |
| Benchmark Date: 2025-09-18 13:17:58 | |
| Model: Detoxify-Medium | |
| Dataset: ParaDetox (https://github.com/s-nlp/paradetox) | |
| Total Samples: 1011 | |
| π― OVERALL PERFORMANCE METRICS | |
| -------------------------------------------------- | |
| Toxicity Reduction: 0.178 | |
| Semantic Preservation: 0.561 | |
| Fluency: 0.929 | |
| Average Latency: 160.2ms | |
| Original Toxicity: 0.196 | |
| Final Toxicity: 0.018 | |
| π DATASET BREAKDOWN | |
| -------------------------------------------------- | |
| πΉ PARADETOX TOXIC NEUTRAL | |
| Samples: 1000 | |
| Toxicity Reduction: 0.044 | |
| Semantic Preservation: 0.645 | |
| Fluency: 0.922 | |
| Latency: 156.2ms | |
| Original Toxicity: 0.051 | |
| Final Toxicity: 0.007 | |
| πΉ PARADETOX HIGH TOXICITY | |
| Samples: 11 | |
| Toxicity Reduction: 0.313 | |
| Semantic Preservation: 0.477 | |
| Fluency: 0.936 | |
| Latency: 164.3ms | |
| Original Toxicity: 0.342 | |
| Final Toxicity: 0.029 | |
| ================================================================================ |