Instructions to use AbdulKader85/ASEMS_Llama with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AbdulKader85/ASEMS_Llama with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AbdulKader85/ASEMS_Llama", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use AbdulKader85/ASEMS_Llama 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 AbdulKader85/ASEMS_Llama:Q4_K_S # Run inference directly in the terminal: llama cli -hf AbdulKader85/ASEMS_Llama:Q4_K_S
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf AbdulKader85/ASEMS_Llama:Q4_K_S # Run inference directly in the terminal: llama cli -hf AbdulKader85/ASEMS_Llama:Q4_K_S
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 AbdulKader85/ASEMS_Llama:Q4_K_S # Run inference directly in the terminal: ./llama-cli -hf AbdulKader85/ASEMS_Llama:Q4_K_S
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 AbdulKader85/ASEMS_Llama:Q4_K_S # Run inference directly in the terminal: ./build/bin/llama-cli -hf AbdulKader85/ASEMS_Llama:Q4_K_S
Use Docker
docker model run hf.co/AbdulKader85/ASEMS_Llama:Q4_K_S
- LM Studio
- Jan
- Ollama
How to use AbdulKader85/ASEMS_Llama with Ollama:
ollama run hf.co/AbdulKader85/ASEMS_Llama:Q4_K_S
- Unsloth Desktop
- Docker Model Runner
How to use AbdulKader85/ASEMS_Llama with Docker Model Runner:
docker model run hf.co/AbdulKader85/ASEMS_Llama:Q4_K_S
- Lemonade
How to use AbdulKader85/ASEMS_Llama with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull AbdulKader85/ASEMS_Llama:Q4_K_S
Run and chat with the model
lemonade run user.ASEMS_Llama-Q4_K_S
List all available models
lemonade list
- Atomic Chat
AbdulKader85/ASEMS_Llama
This model was converted to GGUF format from AbdulKader85/ASEMS_Llamas using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
CLI:
llama-cli --hf-repo AbdulKader85/ASEMS_Llama --hf-file tinyllamaonlowpowereddevices-q4_k_s.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo AbdulKader85/ASEMS_Llama --hf-file tinyllamaonlowpowereddevices-q4_k_s.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.
Step 1: Clone llama.cpp from GitHub.
git clone https://github.com/ggerganov/llama.cpp
Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
cd llama.cpp && LLAMA_CURL=1 make
Step 3: Run inference through the main binary.
./llama-cli --hf-repo AbdulKader85/ASEMS_Llama --hf-file tinyllamaonlowpowereddevices-q4_k_s.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo AbdulKader85/ASEMS_Llama --hf-file tinyllamaonlowpowereddevices-q4_k_s.gguf -c 2048
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Model tree for AbdulKader85/ASEMS_Llama
Base model
meta-llama/Llama-3.2-1B-Instruct