Instructions to use hardlyworking/moooooo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- llama-cpp-python
How to use hardlyworking/moooooo with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="hardlyworking/moooooo", filename="holdmy4b-q4_0.gguf", )
output = llm( "Once upon a time,", max_tokens=512, echo=True ) print(output)
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- llama.cpp
How to use hardlyworking/moooooo with llama.cpp:
Install from brew
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf hardlyworking/moooooo:Q4_0 # Run inference directly in the terminal: llama-cli -hf hardlyworking/moooooo:Q4_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf hardlyworking/moooooo:Q4_0 # Run inference directly in the terminal: llama-cli -hf hardlyworking/moooooo: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 hardlyworking/moooooo:Q4_0 # Run inference directly in the terminal: ./llama-cli -hf hardlyworking/moooooo: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 hardlyworking/moooooo:Q4_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf hardlyworking/moooooo:Q4_0
Use Docker
docker model run hf.co/hardlyworking/moooooo:Q4_0
- LM Studio
- Jan
- Ollama
How to use hardlyworking/moooooo with Ollama:
ollama run hf.co/hardlyworking/moooooo:Q4_0
- Unsloth Studio new
How to use hardlyworking/moooooo 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 hardlyworking/moooooo 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 hardlyworking/moooooo to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for hardlyworking/moooooo to start chatting
- Docker Model Runner
How to use hardlyworking/moooooo with Docker Model Runner:
docker model run hf.co/hardlyworking/moooooo:Q4_0
- Lemonade
How to use hardlyworking/moooooo with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull hardlyworking/moooooo:Q4_0
Run and chat with the model
lemonade run user.moooooo-Q4_0
List all available models
lemonade list
hardlyworking/HoldMy4B-Q4_0-GGUF
This model was converted to GGUF format from hardlyworking/HoldMy4B using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
CLI:
llama-cli --hf-repo hardlyworking/HoldMy4B-Q4_0-GGUF --hf-file holdmy4b-q4_0.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo hardlyworking/HoldMy4B-Q4_0-GGUF --hf-file holdmy4b-q4_0.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.
Step 1: Clone llama.cpp from GitHub.
git clone https://github.com/ggerganov/llama.cpp
Step 2: Move into the llama.cpp folder and build it with LLAMA_CURL=1 flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
cd llama.cpp && LLAMA_CURL=1 make
Step 3: Run inference through the main binary.
./llama-cli --hf-repo hardlyworking/HoldMy4B-Q4_0-GGUF --hf-file holdmy4b-q4_0.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo hardlyworking/HoldMy4B-Q4_0-GGUF --hf-file holdmy4b-q4_0.gguf -c 2048
- Downloads last month
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4-bit
Model tree for hardlyworking/moooooo
Base model
Salesforce/xgen-small-4B-instruct-r
docker model run hf.co/hardlyworking/moooooo:Q4_0