Instructions to use Dabococo/Minecraft_Flans_Mod with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Dabococo/Minecraft_Flans_Mod with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Dabococo/Minecraft_Flans_Mod",
	filename="FullPrecision_WW2-Server_Model.F16.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 Dabococo/Minecraft_Flans_Mod with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Dabococo/Minecraft_Flans_Mod:F16
# Run inference directly in the terminal:
llama-cli -hf Dabococo/Minecraft_Flans_Mod:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Dabococo/Minecraft_Flans_Mod:F16
# Run inference directly in the terminal:
llama-cli -hf Dabococo/Minecraft_Flans_Mod:F16

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 Dabococo/Minecraft_Flans_Mod:F16
# Run inference directly in the terminal:
./llama-cli -hf Dabococo/Minecraft_Flans_Mod:F16

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 Dabococo/Minecraft_Flans_Mod:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Dabococo/Minecraft_Flans_Mod:F16

Use Docker

docker model run hf.co/Dabococo/Minecraft_Flans_Mod:F16

LM Studio
Jan
Ollama
How to use Dabococo/Minecraft_Flans_Mod with Ollama:
```
ollama run hf.co/Dabococo/Minecraft_Flans_Mod:F16
```

Unsloth Studio new

How to use Dabococo/Minecraft_Flans_Mod 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 Dabococo/Minecraft_Flans_Mod 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 Dabococo/Minecraft_Flans_Mod to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Dabococo/Minecraft_Flans_Mod to start chatting

Docker Model Runner
How to use Dabococo/Minecraft_Flans_Mod with Docker Model Runner:
```
docker model run hf.co/Dabococo/Minecraft_Flans_Mod:F16
```

Lemonade

How to use Dabococo/Minecraft_Flans_Mod with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Dabococo/Minecraft_Flans_Mod:F16

Run and chat with the model

lemonade run user.Minecraft_Flans_Mod-F16

List all available models

lemonade list

INFORMATIONS

by Dabococo - opened May 8, 2024

Discussion

Dabococo

Owner May 8, 2024

The Flan’s Mod model is hardly specialized in Flan’s mod and the dataset is tiny. However I foresee an AI model that will best understand ANY HBM Nuclear Tech Mod. This should happen soon (1 week). It will be much better than this one.

Le modèle Flan's Mod n'est quasiment pas spécialisé dans Flan's mod et le dataset est minuscule. Cependant je prévois un modèle d'IA qui comprendra au mieux TOUT HBM Nuclear Tech Mod. Cela devrait arrivé sous peu de temps (1 semaine). Il sera beaucoup beaucoup plus performant que celui ci.

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