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
Upload 2 files
Browse files- .gitattributes +1 -0
- chk-wikichat-256x28-4810.gguf +3 -0
- model_config.json +54 -0
.gitattributes
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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ggml-wikichat-256x28-f32-4810.gguf filter=lfs diff=lfs merge=lfs -text
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ggml-wikichat-256x28-f32-4810.gguf filter=lfs diff=lfs merge=lfs -text
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chk-wikichat-256x28-4810.gguf filter=lfs diff=lfs merge=lfs -text
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chk-wikichat-256x28-4810.gguf
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model_config.json
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{
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"name": "WikiGGML",
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"load_params": {
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"n_ctx": 2048,
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"n_batch": 512,
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"rope_freq_base": 0,
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"rope_freq_scale": 0,
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"n_gpu_layers": -1,
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"use_mlock": true,
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"main_gpu": 0,
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"tensor_split": [
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0
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"seed": -1,
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"f16_kv": true,
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"use_mmap": true,
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"no_kv_offload": false,
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"num_experts_used": 0
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},
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"inference_params": {
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"n_threads": 4,
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"n_predict": -1,
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"top_k": 40,
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"min_p": 0.05,
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"top_p": 0.95,
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"temp": 0.8,
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"repeat_penalty": 1.1,
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"input_prefix": "User:",
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"input_suffix": "\nA:",
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"antiprompt": [
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"### Instruction:",
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"### User:\\n",
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"User:\\n",
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"User:"
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],
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"pre_prompt": "",
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"pre_prompt_suffix": "\\n",
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"pre_prompt_prefix": "",
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"seed": -1,
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"tfs_z": 1,
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"repeat_last_n": 64,
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"mirostat_tau": 5,
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"mirostat_eta": 0.1,
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"memory_f16": true,
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"multiline_input": false,
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"penalize_nl": true
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}
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}
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