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Türkçe dilinde de eğitilmiş, anlamlı ve faydalı Türkçe yanıt verebilen modeller. Llama modelleri Türkçe konusunda pek yeterli değil maalesef. • 38 items • Updated • 2
How to use matrixportalx/Metafor-GGUF with Transformers:
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("matrixportalx/Metafor-GGUF", dtype="auto")How to use matrixportalx/Metafor-GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="matrixportalx/Metafor-GGUF", filename="metafor.q4_0.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
How to use matrixportalx/Metafor-GGUF with llama.cpp:
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf matrixportalx/Metafor-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf matrixportalx/Metafor-GGUF:Q4_K_M
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf matrixportalx/Metafor-GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf matrixportalx/Metafor-GGUF:Q4_K_M
# 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/Metafor-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf matrixportalx/Metafor-GGUF:Q4_K_M
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/Metafor-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf matrixportalx/Metafor-GGUF:Q4_K_M
docker model run hf.co/matrixportalx/Metafor-GGUF:Q4_K_M
How to use matrixportalx/Metafor-GGUF with Ollama:
ollama run hf.co/matrixportalx/Metafor-GGUF:Q4_K_M
How to use matrixportalx/Metafor-GGUF with Unsloth Studio:
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/Metafor-GGUF to start chatting
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/Metafor-GGUF to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for matrixportalx/Metafor-GGUF to start chatting
How to use matrixportalx/Metafor-GGUF with Docker Model Runner:
docker model run hf.co/matrixportalx/Metafor-GGUF:Q4_K_M
How to use matrixportalx/Metafor-GGUF with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull matrixportalx/Metafor-GGUF:Q4_K_M
lemonade run user.Metafor-GGUF-Q4_K_M
lemonade list
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf matrixportalx/Metafor-GGUF:# Run inference directly in the terminal:
llama-cli -hf matrixportalx/Metafor-GGUF:# 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/Metafor-GGUF:# Run inference directly in the terminal:
./llama-cli -hf matrixportalx/Metafor-GGUF: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/Metafor-GGUF:# Run inference directly in the terminal:
./build/bin/llama-cli -hf matrixportalx/Metafor-GGUF:docker model run hf.co/matrixportalx/Metafor-GGUF:| 🚀 Download | 🔢 Type | 📝 Description |
|---|---|---|
| Download | Q4 0 | Standard 4-bit (fast on ARM) |
| Download | Q4 K M | 4-bit balanced (recommended default) |
| Download | Q5 K M | 5-bit best (recommended HQ option) |
💡 Q4 K M provides the best balance for most use cases
4-bit
5-bit
Base model
meta-llama/Meta-Llama-3-8B-Instruct
Install from brew
# Start a local OpenAI-compatible server with a web UI: llama-server -hf matrixportalx/Metafor-GGUF:# Run inference directly in the terminal: llama-cli -hf matrixportalx/Metafor-GGUF: