Instructions to use dreamMaker34/XiXiChat_base_14b-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use dreamMaker34/XiXiChat_base_14b-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 dreamMaker34/XiXiChat_base_14b-GGUF # Run inference directly in the terminal: llama cli -hf dreamMaker34/XiXiChat_base_14b-GGUF
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf dreamMaker34/XiXiChat_base_14b-GGUF # Run inference directly in the terminal: llama cli -hf dreamMaker34/XiXiChat_base_14b-GGUF
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 dreamMaker34/XiXiChat_base_14b-GGUF # Run inference directly in the terminal: ./llama-cli -hf dreamMaker34/XiXiChat_base_14b-GGUF
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 dreamMaker34/XiXiChat_base_14b-GGUF # Run inference directly in the terminal: ./build/bin/llama-cli -hf dreamMaker34/XiXiChat_base_14b-GGUF
Use Docker
docker model run hf.co/dreamMaker34/XiXiChat_base_14b-GGUF
- LM Studio
- Jan
- Ollama
How to use dreamMaker34/XiXiChat_base_14b-GGUF with Ollama:
ollama run hf.co/dreamMaker34/XiXiChat_base_14b-GGUF
- Unsloth Desktop
- Docker Model Runner
How to use dreamMaker34/XiXiChat_base_14b-GGUF with Docker Model Runner:
docker model run hf.co/dreamMaker34/XiXiChat_base_14b-GGUF
- Lemonade
How to use dreamMaker34/XiXiChat_base_14b-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull dreamMaker34/XiXiChat_base_14b-GGUF
Run and chat with the model
lemonade run user.XiXiChat_base_14b-GGUF-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
YAML Metadata Warning:empty or missing yaml metadata in repo card
Check out the documentation for more information.
XiXiChat
Introduction
In Agriculture, several LLMs have been proposed. However, It is a challenging task to make large models simultaneously generalistically recognizable and highly specialized in knowledge. To achieve this goal, our lab tries to design XiXiChat, a doman-specific agriculture large language model, to handle the specialized questions in root crops domain. XiXiChat-14b-Beta has a 14 billion parameter base model and a short Q&A chat model tailored for agricultural scenarios. The current beta version is trained by around specific 50,000 Q&A data.
model configuration
Install Ollama
Run the following command to install Ollama:
curl -fsSL https://ollama.com/install.sh | sh
Open a command prompt and enter ollama --version to verify that the installation was successful.
Download model
Open dreamMaker34/XiXiChat_base_14b-GGUF · Hugging Face, and download XiXiChat_base_14b.gguf locally.
Import model
Write a configuration file named Modelfile:
FROM ./XiXiChat_base_14b.gguf
TEMPLATE """[INST] {{ if .System }}<<SYS>>{{ .System }}<</SYS>>
{{ end }}{{ .Prompt }} [/INST] """
Then, import the model using the following command:
ollama create XiXiChat -f ./Modelfile
After successful import, you can use the list command to view:
$ ollama list
NAME ID SIZE MODIFIED
XiXiChat:latest 0c2168345913 15 GB 18 hours ago
Build a Web environment
Install docker
The installation of docker can be found in this blog post:
https://blog.csdn.net/m82_a1/article/details/98870376
After docker was installed, please start the docker service:
sudo service docker start
Start WebUI
docker run -d --network=host -v open-webui:/app/backend/data -e OLLAMA_BASE_URL=http://127.0.0.1:11434 --name open-webui --restart always ghcr.io/open-webui/open-webui:main
After that, you can access WebUI and use our model at http://localhost:8080.
- Downloads last month
- 7
We're not able to determine the quantization variants.
