Instructions to use SlayThat/NikiAI-Survival 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 SlayThat/NikiAI-Survival 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 SlayThat/NikiAI-Survival # Run inference directly in the terminal: llama cli -hf SlayThat/NikiAI-Survival
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf SlayThat/NikiAI-Survival # Run inference directly in the terminal: llama cli -hf SlayThat/NikiAI-Survival
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 SlayThat/NikiAI-Survival # Run inference directly in the terminal: ./llama-cli -hf SlayThat/NikiAI-Survival
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 SlayThat/NikiAI-Survival # Run inference directly in the terminal: ./build/bin/llama-cli -hf SlayThat/NikiAI-Survival
Use Docker
docker model run hf.co/SlayThat/NikiAI-Survival
- LM Studio
- Jan
- vLLM
How to use SlayThat/NikiAI-Survival with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SlayThat/NikiAI-Survival" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SlayThat/NikiAI-Survival", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/SlayThat/NikiAI-Survival
- Ollama
How to use SlayThat/NikiAI-Survival with Ollama:
ollama run hf.co/SlayThat/NikiAI-Survival
- Unsloth Desktop
- Docker Model Runner
How to use SlayThat/NikiAI-Survival with Docker Model Runner:
docker model run hf.co/SlayThat/NikiAI-Survival
- Lemonade
How to use SlayThat/NikiAI-Survival with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull SlayThat/NikiAI-Survival
Run and chat with the model
lemonade run user.NikiAI-Survival-{{QUANT_TAG}}List all available models
lemonade list
- Atomic Chat
File size: 1,329 Bytes
c7dde04 2a11059 53290e2 | 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 43 44 | ---
license: llama3.2
datasets:
- wikimedia/wikipedia
language:
- en
base_model:
- meta-llama/Llama-3.2-1B
pipeline_tag: text-generation
tags:
- gguf
- unsloth
- survival
- llama-3
- q4_k_m
---
# NikiAI-Survival (GGUF)
**NikiAI-Survival** is a lightweight, domain-adapted language model based on `meta-llama/Llama-3.2-1B`. It is fine-tuned on specialized knowledge covering wilderness survival, first aid, bushcraft, emergency signaling, water purification, and disaster preparedness.
---
## Model Details
* **Developed by:** SlayThat
* **Base Model:** [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B)
* **Fine-Tuning Framework:** [Unsloth](https://github.com/unslothai/unsloth)
* **Format:** GGUF (4-bit medium quantization `Q4_K_M`)
* **Primary Domain:** Survival Skills, Wilderness Medicine, Bushcraft, Emergency Preparedness
---
## How to Run Locally
### Option 1: LM Studio
1. Open **LM Studio**.
2. Drag and drop the downloaded `llama-3.2-1b.Q4_K_M.gguf` file directly into the application.
3. Select the model from the top dropdown menu and start chatting.
### Option 2: Ollama
1. Place the `.gguf` file in a dedicated folder.
2. Create a text file named `Modelfile` in the same directory with this content:
```dockerfile
FROM ./llama-3.2-1b.Q4_K_M.gguf
PARAMETER stop "<|eot_id|>" |