Instructions to use matrixportalx/aya-23-8B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use matrixportalx/aya-23-8B-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("matrixportalx/aya-23-8B-GGUF", dtype="auto") - llama-cpp-python
How to use matrixportalx/aya-23-8B-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="matrixportalx/aya-23-8B-GGUF", filename="aya-23-8b-f16.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use matrixportalx/aya-23-8B-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 matrixportalx/aya-23-8B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf matrixportalx/aya-23-8B-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 matrixportalx/aya-23-8B-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf matrixportalx/aya-23-8B-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 matrixportalx/aya-23-8B-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf matrixportalx/aya-23-8B-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 matrixportalx/aya-23-8B-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf matrixportalx/aya-23-8B-GGUF:Q4_K_M
Use Docker
docker model run hf.co/matrixportalx/aya-23-8B-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use matrixportalx/aya-23-8B-GGUF with Ollama:
ollama run hf.co/matrixportalx/aya-23-8B-GGUF:Q4_K_M
- Unsloth Studio
How to use matrixportalx/aya-23-8B-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 matrixportalx/aya-23-8B-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 matrixportalx/aya-23-8B-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for matrixportalx/aya-23-8B-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use matrixportalx/aya-23-8B-GGUF with Docker Model Runner:
docker model run hf.co/matrixportalx/aya-23-8B-GGUF:Q4_K_M
- Lemonade
How to use matrixportalx/aya-23-8B-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull matrixportalx/aya-23-8B-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.aya-23-8B-GGUF-Q4_K_M
List all available models
lemonade list
metadata
base_model: CohereForAI/aya-23-8B
language:
- en
- fr
- de
- es
- it
- pt
- ja
- ko
- zh
- ar
- el
- fa
- pl
- id
- cs
- he
- hi
- nl
- ro
- ru
- tr
- uk
- vi
library_name: transformers
license: cc-by-nc-4.0
tags:
- llama-cpp
- matrixportal
inference: false
extra_gated_prompt: >-
By submitting this form, you agree to the [License
Agreement](https://cohere.com/c4ai-cc-by-nc-license) and acknowledge that the
information you provide will be collected, used, and shared in accordance with
Cohere’s [Privacy Policy]( https://cohere.com/privacy). You’ll receive email
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I agree to use this model for non-commercial use ONLY: checkbox
matrixportal/aya-23-8B-GGUF
This model was converted to GGUF format from CohereForAI/aya-23-8B using llama.cpp via the ggml.ai's all-gguf-same-where space.
Refer to the original model card for more details on the model.
✅ Quantized Models Download List
✨ Recommended for CPU: Q4_K_M | ⚡ Recommended for ARM CPU: Q4_0 | 🏆 Best Quality: Q8_0
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