Instructions to use AyatBahaa/LSS 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 AyatBahaa/LSS 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 AyatBahaa/LSS:Q4_K_M # Run inference directly in the terminal: llama cli -hf AyatBahaa/LSS:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf AyatBahaa/LSS:Q4_K_M # Run inference directly in the terminal: llama cli -hf AyatBahaa/LSS:Q4_K_M
Build from source code
git clone https://github.com/ggml-org/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-app # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama serve -hf AyatBahaa/LSS:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama cli -hf AyatBahaa/LSS:Q4_K_M
Use Docker
docker model run hf.co/AyatBahaa/LSS:Q4_K_M
- Llama new
- LM Studio
- Jan
- Ollama
How to use AyatBahaa/LSS with Ollama:
ollama run hf.co/AyatBahaa/LSS:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use AyatBahaa/LSS with Docker Model Runner:
docker model run hf.co/AyatBahaa/LSS:Q4_K_M
- Lemonade
How to use AyatBahaa/LSS with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull AyatBahaa/LSS:Q4_K_M
Run and chat with the model
lemonade run user.LSS-Q4_K_M
List all available models
lemonade list
- Atomic Chat
Download Modelfile from AyatBahaa/LSS: direct link, hf CLI and curl.
- Browser
- Download file 500 Bytes
-
https://huggingface.co/AyatBahaa/LSS/resolve/main/Modelfile
- Command line
-
hf download hf://AyatBahaa/LSS/Modelfile
-
curl -L -o Modelfile https://huggingface.co/AyatBahaa/LSS/resolve/main/Modelfile
500 Bytes
| FROM /content/AyatBahaa/LSS/unsloth.F16.gguf | |
| TEMPLATE """Below are the details of a composite material. | |
| Predict the LSS_Name based on its characteristics. | |
| {{ if .Prompt }} | |
| >>> Material Details: | |
| {{ .Prompt }}{{ end }} | |
| >>> What is the LSS_Name? | |
| {{ .Response }}<|end_of_text|>""" | |
| PARAMETER stop "<|start_header_id|>" | |
| PARAMETER stop "<|end_header_id|>" | |
| PARAMETER stop "<|eot_id|>" | |
| PARAMETER stop "<|end_of_text|>" | |
| PARAMETER stop "<|reserved_special_token_" | |
| PARAMETER temperature 1.5 | |
| PARAMETER min_p 0.1 |