Text Generation
GGUF
llama.cpp
quantized
llama-cpp
imatrix
llama
spanish
multilingual
european
sovereign-ai
kld-measured
conversational
Instructions to use KikoCis/ALIA-40b-instruct-2601-GGUF 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 KikoCis/ALIA-40b-instruct-2601-GGUF 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 KikoCis/ALIA-40b-instruct-2601-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf KikoCis/ALIA-40b-instruct-2601-GGUF:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf KikoCis/ALIA-40b-instruct-2601-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf KikoCis/ALIA-40b-instruct-2601-GGUF:Q4_K_M
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 KikoCis/ALIA-40b-instruct-2601-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf KikoCis/ALIA-40b-instruct-2601-GGUF:Q4_K_M
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 KikoCis/ALIA-40b-instruct-2601-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf KikoCis/ALIA-40b-instruct-2601-GGUF:Q4_K_M
Use Docker
docker model run hf.co/KikoCis/ALIA-40b-instruct-2601-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use KikoCis/ALIA-40b-instruct-2601-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "KikoCis/ALIA-40b-instruct-2601-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "KikoCis/ALIA-40b-instruct-2601-GGUF", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/KikoCis/ALIA-40b-instruct-2601-GGUF:Q4_K_M
- Ollama
How to use KikoCis/ALIA-40b-instruct-2601-GGUF with Ollama:
ollama run hf.co/KikoCis/ALIA-40b-instruct-2601-GGUF:Q4_K_M
- Unsloth Studio
How to use KikoCis/ALIA-40b-instruct-2601-GGUF 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 KikoCis/ALIA-40b-instruct-2601-GGUF 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 KikoCis/ALIA-40b-instruct-2601-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for KikoCis/ALIA-40b-instruct-2601-GGUF to start chatting
- Docker Model Runner
How to use KikoCis/ALIA-40b-instruct-2601-GGUF with Docker Model Runner:
docker model run hf.co/KikoCis/ALIA-40b-instruct-2601-GGUF:Q4_K_M
- Lemonade
How to use KikoCis/ALIA-40b-instruct-2601-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull KikoCis/ALIA-40b-instruct-2601-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.ALIA-40b-instruct-2601-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
| 93a1911cc96ac4baaa46ced7a5803aa9f146e42e7309e2d9eac15de998b9863c ALIA-40b-instruct-2601-IQ2_M.gguf | |
| b7d2574c73f8ee77a8a03cb58ee19a05e23fb9b838c7a56ea892901c38249731 ALIA-40b-instruct-2601-Q3_K_M.gguf | |
| 4223e3095093b6d46155a66bc68a146022d045bbc1591c4c5f6c6561a0079415 ALIA-40b-instruct-2601-Q4_K_M.gguf | |
| 7b2ea52aded470967b6ff7247c1f1d1eb5a7d38a52f68f671bfd342a9722e8c9 ALIA-40b-instruct-2601-Q5_K_M.gguf | |
| 47f1d78087d5d6ca127692dcaf9b5ce0f92a36b87ee5f60bba41a50905c9020d ALIA-40b-instruct-2601-Q8_0.gguf | |
| dbf52de4a8d47693813d871024747eb6e573a434f84499b9f40ee9db767a4c88 banner.png | |
| 4a113f999267807af453ed87224c99670f53c97b56f89f30b7f3825575666689 alia-40b-es.imatrix | |
| 8026c336b80e1d11bacd7194af3bce0e004b70b499587dbd3057a4957661e422 metrics/quant-summary.csv | |
| SHA_DONE | |