Instructions to use iandennismiller/samantha-1.1-llama-33b-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 iandennismiller/samantha-1.1-llama-33b-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 iandennismiller/samantha-1.1-llama-33b-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf iandennismiller/samantha-1.1-llama-33b-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 iandennismiller/samantha-1.1-llama-33b-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf iandennismiller/samantha-1.1-llama-33b-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 iandennismiller/samantha-1.1-llama-33b-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf iandennismiller/samantha-1.1-llama-33b-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 iandennismiller/samantha-1.1-llama-33b-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf iandennismiller/samantha-1.1-llama-33b-GGUF:Q4_K_M
Use Docker
docker model run hf.co/iandennismiller/samantha-1.1-llama-33b-GGUF:Q4_K_M
- LM Studio
- Jan
- Ollama
How to use iandennismiller/samantha-1.1-llama-33b-GGUF with Ollama:
ollama run hf.co/iandennismiller/samantha-1.1-llama-33b-GGUF:Q4_K_M
- Unsloth Studio
How to use iandennismiller/samantha-1.1-llama-33b-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 iandennismiller/samantha-1.1-llama-33b-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 iandennismiller/samantha-1.1-llama-33b-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for iandennismiller/samantha-1.1-llama-33b-GGUF to start chatting
- Atomic Chat new
- Docker Model Runner
How to use iandennismiller/samantha-1.1-llama-33b-GGUF with Docker Model Runner:
docker model run hf.co/iandennismiller/samantha-1.1-llama-33b-GGUF:Q4_K_M
- Lemonade
How to use iandennismiller/samantha-1.1-llama-33b-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull iandennismiller/samantha-1.1-llama-33b-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.samantha-1.1-llama-33b-GGUF-Q4_K_M
List all available models
lemonade list
Eric Hartford's Samantha 1.1 Llama 33B GGUF
Samantha 1.1 is a very smart model. For those of us with 24gb usable RAM (including Apple Silicon with 32gb RAM), this is just about the best model available as of October, 2023.
I've converted the model to GGUF for the sake of compatibility. Currently, only Q4_K_S is available because that's the largest model that runs in 24gb.
For more information, see Eric Hartford's Samantha 1.1 Llama 33B. To examine the original quant, see TheBloke/samantha-1.1-llama-33B-GGML
The particular quants selected for this repo are in support of calm, which is a language model runner that automatically uses the right prompts, templates, context size, etc.
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Model tree for iandennismiller/samantha-1.1-llama-33b-GGUF
Base model
QuixiAI/samantha-1.1-llama-33b
docker model run hf.co/iandennismiller/samantha-1.1-llama-33b-GGUF: