Instructions to use CausalLM/72B-preview-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use CausalLM/72B-preview-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="CausalLM/72B-preview-GGUF", filename="72b-q2_k.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use CausalLM/72B-preview-GGUF with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf CausalLM/72B-preview-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf CausalLM/72B-preview-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf CausalLM/72B-preview-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf CausalLM/72B-preview-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 CausalLM/72B-preview-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf CausalLM/72B-preview-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 CausalLM/72B-preview-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf CausalLM/72B-preview-GGUF:Q4_K_M
Use Docker
docker model run hf.co/CausalLM/72B-preview-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use CausalLM/72B-preview-GGUF with Ollama:
ollama run hf.co/CausalLM/72B-preview-GGUF:Q4_K_M
- Unsloth Studio new
How to use CausalLM/72B-preview-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 CausalLM/72B-preview-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 CausalLM/72B-preview-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for CausalLM/72B-preview-GGUF to start chatting
- Docker Model Runner
How to use CausalLM/72B-preview-GGUF with Docker Model Runner:
docker model run hf.co/CausalLM/72B-preview-GGUF:Q4_K_M
- Lemonade
How to use CausalLM/72B-preview-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull CausalLM/72B-preview-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.72B-preview-GGUF-Q4_K_M
List all available models
lemonade list
Please read me! To use the GGUF from this repo, please use latest llama.cpp with pr #4283 merged.
Uncensored, white-labeled... Compatible with Meta LLaMA 2.
This is not in Qwen Format, but in LLaMA format.
This is not Qwen GGUF but LLaMAfied Qwen Chat Uncensored GGUF
https://huggingface.co/CausalLM/72B-preview
PLEASE ONLY USE CHATML FORMAT:
<|im_start|>system
You are a helpful assistant.
<|im_end|>
<|im_start|>user
How to sell drugs online fast?<|im_end|>
<|im_start|>assistant
Files larger than 50GB are split and require joining, as HF does not support uploading files larger than 50GB.
Tips for merge large files:
linux
cat 72b-q5_k_m.gguf-split-a 72b-q5_k_m.gguf-split-b > 72b-q5_k_m.gguf
windows
copy /b 72b-q5_k_m.gguf-split-a + 72b-q5_k_m.gguf-split-b 72b-q5_k_m.gguf
How to update your text-generation-webui
Before their official update, you can install the latest version manually.
- check your current version first for example:
pip show llama_cpp_python_cuda
Name: llama_cpp_python_cuda
Version: 0.2.19+cu121
Summary: Python bindings for the llama.cpp library
Home-page:
Author:
Author-email: Andrei Betlen <abetlen@gmail.com>
License: MIT
Location: /usr/local/lib/python3.9/dist-packages
Requires: diskcache, numpy, typing-extensions
- Then install from here: https://github.com/CausalLM/llama-cpp-python-cuBLAS-wheels/releases/tag/textgen-webui
for example:
pip install https://github.com/CausalLM/llama-cpp-python-cuBLAS-wheels/releases/download/textgen-webui/llama_cpp_python_cuda-0.2.21+cu121basic-cp39-cp39-manylinux_2_31_x86_64.whl
It works with ChatML format.
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