Instructions to use EXCO123/admdk4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use EXCO123/admdk4 with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="EXCO123/admdk4", filename="models/admdk4-q4_0.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use EXCO123/admdk4 with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf EXCO123/admdk4:Q4_0 # Run inference directly in the terminal: llama-cli -hf EXCO123/admdk4:Q4_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf EXCO123/admdk4:Q4_0 # Run inference directly in the terminal: llama-cli -hf EXCO123/admdk4:Q4_0
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 EXCO123/admdk4:Q4_0 # Run inference directly in the terminal: ./llama-cli -hf EXCO123/admdk4:Q4_0
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 EXCO123/admdk4:Q4_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf EXCO123/admdk4:Q4_0
Use Docker
docker model run hf.co/EXCO123/admdk4:Q4_0
- LM Studio
- Jan
- Ollama
How to use EXCO123/admdk4 with Ollama:
ollama run hf.co/EXCO123/admdk4:Q4_0
- Unsloth Studio new
How to use EXCO123/admdk4 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 EXCO123/admdk4 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 EXCO123/admdk4 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for EXCO123/admdk4 to start chatting
- Docker Model Runner
How to use EXCO123/admdk4 with Docker Model Runner:
docker model run hf.co/EXCO123/admdk4:Q4_0
- Lemonade
How to use EXCO123/admdk4 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull EXCO123/admdk4:Q4_0
Run and chat with the model
lemonade run user.admdk4-Q4_0
List all available models
lemonade list
| { | |
| "_name_or_path": "HuggingFaceTB/SmolLM2-360M-Instruct", | |
| "architectures": [ | |
| "LlamaForCausalLM" | |
| ], | |
| "attention_bias": false, | |
| "attention_dropout": 0.0, | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "head_dim": 64, | |
| "hidden_act": "silu", | |
| "hidden_size": 960, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 2560, | |
| "is_llama_config": true, | |
| "max_position_embeddings": 8192, | |
| "mlp_bias": false, | |
| "model_type": "llama", | |
| "num_attention_heads": 15, | |
| "num_hidden_layers": 32, | |
| "num_key_value_heads": 5, | |
| "pad_token_id": 2, | |
| "pretraining_tp": 1, | |
| "rms_norm_eps": 1e-05, | |
| "rope_interleaved": false, | |
| "rope_scaling": null, | |
| "rope_theta": 100000, | |
| "tie_word_embeddings": true, | |
| "torch_dtype": "float32", | |
| "transformers.js_config": { | |
| "kv_cache_dtype": { | |
| "fp16": "float16", | |
| "q4f16": "float16" | |
| } | |
| }, | |
| "transformers_version": "4.47.0", | |
| "use_cache": true, | |
| "vocab_size": 49152 | |
| } | |