Instructions to use bartowski/labradorite-13b-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 bartowski/labradorite-13b-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 bartowski/labradorite-13b-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf bartowski/labradorite-13b-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 bartowski/labradorite-13b-GGUF:Q4_K_M # Run inference directly in the terminal: llama cli -hf bartowski/labradorite-13b-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 bartowski/labradorite-13b-GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf bartowski/labradorite-13b-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 bartowski/labradorite-13b-GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf bartowski/labradorite-13b-GGUF:Q4_K_M
Use Docker
docker model run hf.co/bartowski/labradorite-13b-GGUF:Q4_K_M
- LM Studio
- Jan
- vLLM
How to use bartowski/labradorite-13b-GGUF with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bartowski/labradorite-13b-GGUF" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "bartowski/labradorite-13b-GGUF", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/bartowski/labradorite-13b-GGUF:Q4_K_M
- Ollama
How to use bartowski/labradorite-13b-GGUF with Ollama:
ollama run hf.co/bartowski/labradorite-13b-GGUF:Q4_K_M
- Unsloth Desktop
- Docker Model Runner
How to use bartowski/labradorite-13b-GGUF with Docker Model Runner:
docker model run hf.co/bartowski/labradorite-13b-GGUF:Q4_K_M
- Lemonade
How to use bartowski/labradorite-13b-GGUF with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull bartowski/labradorite-13b-GGUF:Q4_K_M
Run and chat with the model
lemonade run user.labradorite-13b-GGUF-Q4_K_M
List all available models
lemonade list
- Atomic Chat
File size: 2,957 Bytes
0969b3f | 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 | ---
pipeline_tag: text-generation
tags:
- labradorite
- llama
- llama-2
- ibm
- lab
- labrador
- merlinite
license: llama2
license_link: https://ai.meta.com/llama/license/
language:
- en
quantized_by: bartowski
---
## Llamacpp Quantizations of labradorite-13b
Using <a href="https://github.com/ggerganov/llama.cpp/commit/fa974646e1a2024fc7dc9e6f27cf1f2f5d4a3763">llama.cpp commit fa97464</a> for quantization.
Original model: https://huggingface.co/ibm/labradorite-13b
Download a file (not the whole branch) from below:
| Filename | Quant type | File Size | Description |
| -------- | ---------- | --------- | ----------- |
| [labradorite-13b-Q8_0.gguf](https://huggingface.co/bartowski/labradorite-13b-GGUF/blob/main/labradorite-13b-Q8_0.gguf) | Q8_0 | 13.83GB | Extremely high quality, generally unneeded but max available quant. |
| [labradorite-13b-Q6_K.gguf](https://huggingface.co/bartowski/labradorite-13b-GGUF/blob/main/labradorite-13b-Q6_K.gguf) | Q6_K | 10.67GB | Very high quality, near perfect, *recommended*. |
| [labradorite-13b-Q5_K_M.gguf](https://huggingface.co/bartowski/labradorite-13b-GGUF/blob/main/labradorite-13b-Q5_K_M.gguf) | Q5_K_M | 9.22GB | High quality, very usable. |
| [labradorite-13b-Q5_K_S.gguf](https://huggingface.co/bartowski/labradorite-13b-GGUF/blob/main/labradorite-13b-Q5_K_S.gguf) | Q5_K_S | 8.97GB | High quality, very usable. |
| [labradorite-13b-Q5_0.gguf](https://huggingface.co/bartowski/labradorite-13b-GGUF/blob/main/labradorite-13b-Q5_0.gguf) | Q5_0 | 8.97GB | High quality, older format, generally not recommended. |
| [labradorite-13b-Q4_K_M.gguf](https://huggingface.co/bartowski/labradorite-13b-GGUF/blob/main/labradorite-13b-Q4_K_M.gguf) | Q4_K_M | 7.86GB | Good quality, similar to 4.25 bpw. |
| [labradorite-13b-Q4_K_S.gguf](https://huggingface.co/bartowski/labradorite-13b-GGUF/blob/main/labradorite-13b-Q4_K_S.gguf) | Q4_K_S | 7.42GB | Slightly lower quality with small space savings. |
| [labradorite-13b-Q4_0.gguf](https://huggingface.co/bartowski/labradorite-13b-GGUF/blob/main/labradorite-13b-Q4_0.gguf) | Q4_0 | 7.36GB | Decent quality, older format, generally not recommended. |
| [labradorite-13b-Q3_K_L.gguf](https://huggingface.co/bartowski/labradorite-13b-GGUF/blob/main/labradorite-13b-Q3_K_L.gguf) | Q3_K_L | 6.92GB | Lower quality but usable, good for low RAM availability. |
| [labradorite-13b-Q3_K_M.gguf](https://huggingface.co/bartowski/labradorite-13b-GGUF/blob/main/labradorite-13b-Q3_K_M.gguf) | Q3_K_M | 6.33GB | Even lower quality. |
| [labradorite-13b-Q3_K_S.gguf](https://huggingface.co/bartowski/labradorite-13b-GGUF/blob/main/labradorite-13b-Q3_K_S.gguf) | Q3_K_S | 5.65GB | Low quality, not recommended. |
| [labradorite-13b-Q2_K.gguf](https://huggingface.co/bartowski/labradorite-13b-GGUF/blob/main/labradorite-13b-Q2_K.gguf) | Q2_K | 4.85GB | Extremely low quality, *not* recommended.
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