Instructions to use Monike123/LLaMAbyte-DS_v8 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 Monike123/LLaMAbyte-DS_v8 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 Monike123/LLaMAbyte-DS_v8:Q4_K_M # Run inference directly in the terminal: llama cli -hf Monike123/LLaMAbyte-DS_v8:Q4_K_M
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf Monike123/LLaMAbyte-DS_v8:Q4_K_M # Run inference directly in the terminal: llama cli -hf Monike123/LLaMAbyte-DS_v8: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 Monike123/LLaMAbyte-DS_v8:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf Monike123/LLaMAbyte-DS_v8: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 Monike123/LLaMAbyte-DS_v8:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf Monike123/LLaMAbyte-DS_v8:Q4_K_M
Use Docker
docker model run hf.co/Monike123/LLaMAbyte-DS_v8:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use Monike123/LLaMAbyte-DS_v8 with Ollama:
ollama run hf.co/Monike123/LLaMAbyte-DS_v8:Q4_K_M
- Unsloth Studio
How to use Monike123/LLaMAbyte-DS_v8 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 Monike123/LLaMAbyte-DS_v8 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 Monike123/LLaMAbyte-DS_v8 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for Monike123/LLaMAbyte-DS_v8 to start chatting
- Docker Model Runner
How to use Monike123/LLaMAbyte-DS_v8 with Docker Model Runner:
docker model run hf.co/Monike123/LLaMAbyte-DS_v8:Q4_K_M
- Lemonade
How to use Monike123/LLaMAbyte-DS_v8 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull Monike123/LLaMAbyte-DS_v8:Q4_K_M
Run and chat with the model
lemonade run user.LLaMAbyte-DS_v8-Q4_K_M
List all available models
lemonade list
- Atomic Chat
File size: 631 Bytes
5b3febc edc0d97 5b3febc edc0d97 5b3febc edc0d97 5b3febc edc0d97 5b3febc edc0d97 5b3febc edc0d97 5b3febc edc0d97 5b3febc edc0d97 5b3febc edc0d97 5b3febc edc0d97 5b3febc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 | [
{
"step": 100,
"eval_loss": 0.48696422576904297
},
{
"step": 200,
"eval_loss": 0.34586554765701294
},
{
"step": 300,
"eval_loss": 0.28842663764953613
},
{
"step": 400,
"eval_loss": 0.2540067136287689
},
{
"step": 500,
"eval_loss": 0.2295776903629303
},
{
"step": 600,
"eval_loss": 0.21396693587303162
},
{
"step": 700,
"eval_loss": 0.19977937638759613
},
{
"step": 800,
"eval_loss": 0.19195251166820526
},
{
"step": 900,
"eval_loss": 0.18890142440795898
},
{
"step": 1000,
"eval_loss": 0.18816642463207245
}
] |