Text Generation
Transformers
Safetensors
qwen2
godot
gdscript
qlora
game-development
conversational
text-generation-inference
Instructions to use khursheed/VibeGame-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use khursheed/VibeGame-8B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="khursheed/VibeGame-8B") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("khursheed/VibeGame-8B") model = AutoModelForCausalLM.from_pretrained("khursheed/VibeGame-8B", device_map="auto") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=256) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use khursheed/VibeGame-8B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "khursheed/VibeGame-8B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "khursheed/VibeGame-8B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/khursheed/VibeGame-8B
- SGLang
How to use khursheed/VibeGame-8B with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "khursheed/VibeGame-8B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "khursheed/VibeGame-8B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "khursheed/VibeGame-8B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "khursheed/VibeGame-8B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use khursheed/VibeGame-8B with Docker Model Runner:
docker model run hf.co/khursheed/VibeGame-8B
Download code/scripts/install_godot.py from khursheed/VibeGame-8B: direct link, hf CLI and curl.
- Browser
- Download file 2.55 kB
-
https://huggingface.co/khursheed/VibeGame-8B/resolve/main/code/scripts/install_godot.py
- Command line
-
hf download hf://khursheed/VibeGame-8B/code/scripts/install_godot.py
-
curl -L -o install_godot.py https://huggingface.co/khursheed/VibeGame-8B/resolve/main/code/scripts/install_godot.py
2.55 kB
| #!/usr/bin/env python3 | |
| """Install a checksum-pinned official Godot 4 editor (includes headless mode).""" | |
| import argparse | |
| import hashlib | |
| import json | |
| import os | |
| from pathlib import Path | |
| import platform | |
| import stat | |
| import urllib.request | |
| import zipfile | |
| VERSION = "4.5.1-stable" | |
| ASSETS = { | |
| "Darwin": ("Godot_v4.5.1-stable_macos.universal.zip", "65c27959d02aaacfc131ec7ecb90179ba8045200cb02982bf2be96d117010b8a", "Godot.app/Contents/MacOS/Godot"), | |
| "Linux": ("Godot_v4.5.1-stable_linux.x86_64.zip", "02ec53d1cc7dbb9cc6355393c61b9ab43d1244751a124f10248a4802830788cd", "Godot_v4.5.1-stable_linux.x86_64"), | |
| } | |
| def install(destination: Path) -> Path: | |
| system = platform.system() | |
| if system not in ASSETS or (system == "Linux" and platform.machine() not in ("x86_64", "AMD64")): | |
| raise RuntimeError("Only macOS universal and Linux x86_64 are supported") | |
| filename, expected, relative = ASSETS[system] | |
| destination = destination.expanduser().resolve() | |
| destination.mkdir(parents=True, exist_ok=True) | |
| archive = destination / filename | |
| url = f"https://github.com/godotengine/godot-builds/releases/download/{VERSION}/{filename}" | |
| if not archive.exists(): | |
| temporary = archive.with_suffix(".download") | |
| urllib.request.urlretrieve(url, temporary) | |
| temporary.replace(archive) | |
| actual = hashlib.sha256(archive.read_bytes()).hexdigest() | |
| if actual != expected: | |
| raise RuntimeError(f"Godot archive checksum mismatch: {archive}; remove and retry") | |
| binary = destination / relative | |
| if not binary.exists(): | |
| with zipfile.ZipFile(archive) as zf: | |
| for member in zf.infolist(): | |
| candidate = (destination / member.filename).resolve() | |
| if not candidate.is_relative_to(destination): | |
| raise RuntimeError("Unsafe archive path") | |
| mode = member.external_attr >> 16 | |
| if stat.S_ISLNK(mode): | |
| raise RuntimeError("Unexpected archive symlink") | |
| zf.extractall(destination) | |
| binary.chmod(0o755) | |
| (destination / "installation.json").write_text(json.dumps({"version": VERSION, "url": url, "archive_sha256": actual, "binary_sha256": hashlib.sha256(binary.read_bytes()).hexdigest(), "binary": str(binary)}, indent=2) + "\n") | |
| return binary | |
| if __name__ == "__main__": | |
| parser = argparse.ArgumentParser(description=__doc__) | |
| parser.add_argument("--destination", type=Path, default=Path(".tools/godot")) | |
| args = parser.parse_args() | |
| print(install(args.destination)) | |