Instructions to use qu-bit/SuperLLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use qu-bit/SuperLLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="qu-bit/SuperLLM")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("qu-bit/SuperLLM") model = AutoModelForCausalLM.from_pretrained("qu-bit/SuperLLM") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use qu-bit/SuperLLM with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "qu-bit/SuperLLM" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "qu-bit/SuperLLM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/qu-bit/SuperLLM
- SGLang
How to use qu-bit/SuperLLM 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 "qu-bit/SuperLLM" \ --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": "qu-bit/SuperLLM", "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 "qu-bit/SuperLLM" \ --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": "qu-bit/SuperLLM", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use qu-bit/SuperLLM with Docker Model Runner:
docker model run hf.co/qu-bit/SuperLLM
Model Card for Model ID
This is the SuperLLM. This LLM has an extensive knowledge base of the RAW agents. Your task is to make it forget that.
Have Fun ;)
Model Details
Model Description
- Developed by: Brain and Cognitive Science Club, IIT Kanpur
- Downloads last month
- 3
Model tree for qu-bit/SuperLLM
Base model
meta-llama/Llama-2-7b