Instructions to use leafspark/wikichat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leafspark/wikichat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="leafspark/wikichat")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("leafspark/wikichat", dtype="auto") - llama-cpp-python
How to use leafspark/wikichat with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="leafspark/wikichat", filename="chk-wikichat-256x28-4810.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 leafspark/wikichat with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf leafspark/wikichat:F32 # Run inference directly in the terminal: llama-cli -hf leafspark/wikichat:F32
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf leafspark/wikichat:F32 # Run inference directly in the terminal: llama-cli -hf leafspark/wikichat:F32
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 leafspark/wikichat:F32 # Run inference directly in the terminal: ./llama-cli -hf leafspark/wikichat:F32
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 leafspark/wikichat:F32 # Run inference directly in the terminal: ./build/bin/llama-cli -hf leafspark/wikichat:F32
Use Docker
docker model run hf.co/leafspark/wikichat:F32
- LM Studio
- Jan
- vLLM
How to use leafspark/wikichat with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "leafspark/wikichat" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "leafspark/wikichat", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/leafspark/wikichat:F32
- SGLang
How to use leafspark/wikichat with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "leafspark/wikichat" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "leafspark/wikichat", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "leafspark/wikichat" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "leafspark/wikichat", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Ollama
How to use leafspark/wikichat with Ollama:
ollama run hf.co/leafspark/wikichat:F32
- Unsloth Studio new
How to use leafspark/wikichat 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 leafspark/wikichat 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 leafspark/wikichat to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for leafspark/wikichat to start chatting
- Docker Model Runner
How to use leafspark/wikichat with Docker Model Runner:
docker model run hf.co/leafspark/wikichat:F32
- Lemonade
How to use leafspark/wikichat with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull leafspark/wikichat:F32
Run and chat with the model
lemonade run user.wikichat-F32
List all available models
lemonade list
| { | |
| "name": "WikiGGML", | |
| "load_params": { | |
| "n_ctx": 2048, | |
| "n_batch": 512, | |
| "rope_freq_base": 0, | |
| "rope_freq_scale": 0, | |
| "n_gpu_layers": -1, | |
| "use_mlock": true, | |
| "main_gpu": 0, | |
| "tensor_split": [ | |
| 0 | |
| ], | |
| "seed": -1, | |
| "f16_kv": true, | |
| "use_mmap": true, | |
| "no_kv_offload": false, | |
| "num_experts_used": 0 | |
| }, | |
| "inference_params": { | |
| "n_threads": 4, | |
| "n_predict": -1, | |
| "top_k": 40, | |
| "min_p": 0.05, | |
| "top_p": 0.95, | |
| "temp": 0.8, | |
| "repeat_penalty": 1.1, | |
| "input_prefix": "User:", | |
| "input_suffix": "\nA:", | |
| "antiprompt": [ | |
| "### Instruction:", | |
| "### User:\\n", | |
| "User:\\n", | |
| "User:" | |
| ], | |
| "pre_prompt": "", | |
| "pre_prompt_suffix": "\\n", | |
| "pre_prompt_prefix": "", | |
| "seed": -1, | |
| "tfs_z": 1, | |
| "typical_p": 1, | |
| "repeat_last_n": 64, | |
| "frequency_penalty": 0, | |
| "presence_penalty": 0, | |
| "n_keep": 0, | |
| "logit_bias": {}, | |
| "mirostat": 0, | |
| "mirostat_tau": 5, | |
| "mirostat_eta": 0.1, | |
| "memory_f16": true, | |
| "multiline_input": false, | |
| "penalize_nl": true | |
| } | |
| } |