Instructions to use DavidAU/MN-Dark-Planet-TITAN-12B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DavidAU/MN-Dark-Planet-TITAN-12B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="DavidAU/MN-Dark-Planet-TITAN-12B")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("DavidAU/MN-Dark-Planet-TITAN-12B") model = AutoModelForCausalLM.from_pretrained("DavidAU/MN-Dark-Planet-TITAN-12B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use DavidAU/MN-Dark-Planet-TITAN-12B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "DavidAU/MN-Dark-Planet-TITAN-12B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DavidAU/MN-Dark-Planet-TITAN-12B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/DavidAU/MN-Dark-Planet-TITAN-12B
- SGLang
How to use DavidAU/MN-Dark-Planet-TITAN-12B 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 "DavidAU/MN-Dark-Planet-TITAN-12B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DavidAU/MN-Dark-Planet-TITAN-12B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "DavidAU/MN-Dark-Planet-TITAN-12B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DavidAU/MN-Dark-Planet-TITAN-12B", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use DavidAU/MN-Dark-Planet-TITAN-12B with Docker Model Runner:
docker model run hf.co/DavidAU/MN-Dark-Planet-TITAN-12B
Download model-00002-of-00025.safetensors from DavidAU/MN-Dark-Planet-TITAN-12B: direct link, hf CLI and curl.
- Browser
- Download file 1.34 GB
-
https://huggingface.co/DavidAU/MN-Dark-Planet-TITAN-12B/resolve/main/model-00002-of-00025.safetensors
- Command line
-
hf download hf://DavidAU/MN-Dark-Planet-TITAN-12B/model-00002-of-00025.safetensors
-
curl -L -o model-00002-of-00025.safetensors https://huggingface.co/DavidAU/MN-Dark-Planet-TITAN-12B/resolve/main/model-00002-of-00025.safetensors
1.34 GB
- Xet hash:
- d0d4f2a0fe853e7b4b376003c57ed121de9852d04f8bb77d353cb08b61e35deb
- Size of remote file:
- 1.34 GB
- SHA256:
- 01b153c7ae8343e7afaefd05d96ddefcf136831a493c2b9ad3b14ac84603f595
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