Instructions to use tevykuch/sl0th with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tevykuch/sl0th with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tevykuch/sl0th", dtype="auto") - llama-cpp-python
How to use tevykuch/sl0th with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="tevykuch/sl0th", filename="sl0th-unsloth.F16.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 tevykuch/sl0th with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf tevykuch/sl0th:F16 # Run inference directly in the terminal: llama-cli -hf tevykuch/sl0th:F16
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf tevykuch/sl0th:F16 # Run inference directly in the terminal: llama-cli -hf tevykuch/sl0th:F16
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 tevykuch/sl0th:F16 # Run inference directly in the terminal: ./llama-cli -hf tevykuch/sl0th:F16
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 tevykuch/sl0th:F16 # Run inference directly in the terminal: ./build/bin/llama-cli -hf tevykuch/sl0th:F16
Use Docker
docker model run hf.co/tevykuch/sl0th:F16
- LM Studio
- Jan
- Ollama
How to use tevykuch/sl0th with Ollama:
ollama run hf.co/tevykuch/sl0th:F16
- Unsloth Studio new
How to use tevykuch/sl0th 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 tevykuch/sl0th 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 tevykuch/sl0th to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for tevykuch/sl0th to start chatting
- Docker Model Runner
How to use tevykuch/sl0th with Docker Model Runner:
docker model run hf.co/tevykuch/sl0th:F16
- Lemonade
How to use tevykuch/sl0th with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull tevykuch/sl0th:F16
Run and chat with the model
lemonade run user.sl0th-F16
List all available models
lemonade list
File size: 971 Bytes
64593c9 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 | {
"add_bos_token": true,
"add_eos_token": false,
"added_tokens_decoder": {
"0": {
"content": "<unk>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"1": {
"content": "<s>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
},
"2": {
"content": "</s>",
"lstrip": false,
"normalized": false,
"rstrip": false,
"single_word": false,
"special": true
}
},
"additional_special_tokens": [],
"bos_token": "<s>",
"clean_up_tokenization_spaces": false,
"eos_token": "</s>",
"legacy": true,
"model_max_length": 32768,
"pad_token": "<unk>",
"padding_side": "right",
"sp_model_kwargs": {},
"spaces_between_special_tokens": false,
"tokenizer_class": "LlamaTokenizer",
"unk_token": "<unk>",
"use_default_system_prompt": false
}
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