Instructions to use TheBloke/WizardLM-7B-uncensored-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheBloke/WizardLM-7B-uncensored-GGUF with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TheBloke/WizardLM-7B-uncensored-GGUF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use TheBloke/WizardLM-7B-uncensored-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 TheBloke/WizardLM-7B-uncensored-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf TheBloke/WizardLM-7B-uncensored-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 TheBloke/WizardLM-7B-uncensored-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf TheBloke/WizardLM-7B-uncensored-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 TheBloke/WizardLM-7B-uncensored-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf TheBloke/WizardLM-7B-uncensored-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 TheBloke/WizardLM-7B-uncensored-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf TheBloke/WizardLM-7B-uncensored-GGUF:Q4_K_M
Use Docker
docker model run hf.co/TheBloke/WizardLM-7B-uncensored-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use TheBloke/WizardLM-7B-uncensored-GGUF with Ollama:
ollama run hf.co/TheBloke/WizardLM-7B-uncensored-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use TheBloke/WizardLM-7B-uncensored-GGUF with Docker Model Runner:
docker model run hf.co/TheBloke/WizardLM-7B-uncensored-GGUF:Q4_K_M
- Lemonade
How to use TheBloke/WizardLM-7B-uncensored-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull TheBloke/WizardLM-7B-uncensored-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.WizardLM-7B-uncensored-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Download WizardLM-7B-uncensored.Q6_K.gguf from TheBloke/WizardLM-7B-uncensored-GGUF: direct link, hf CLI and curl.
- Browser
- Download file 5.53 GB
-
https://huggingface.co/TheBloke/WizardLM-7B-uncensored-GGUF/resolve/main/WizardLM-7B-uncensored.Q6_K.gguf
- Command line
-
hf download hf://TheBloke/WizardLM-7B-uncensored-GGUF/WizardLM-7B-uncensored.Q6_K.gguf
-
curl -L -o WizardLM-7B-uncensored.Q6_K.gguf https://huggingface.co/TheBloke/WizardLM-7B-uncensored-GGUF/resolve/main/WizardLM-7B-uncensored.Q6_K.gguf
5.53 GB
- Xet hash:
- 896ca284f8f1aacfa99ae4e861b0929934b77e7f98f0cb89361c4bb955411aa9
- Size of remote file:
- 5.53 GB
- SHA256:
- 22dc0aed32df986c881cf5292453873faf7579876e3e99be93529bcb02aa1d40
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.