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", device_map="auto") - 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
| language: | |
| - en | |
| metrics: | |
| - accuracy | |
| - bleu | |
| - rouge | |
| - glue | |
| base_model: meta-llama/Llama-2-7b | |
| # Model Card for Model ID | |
| <!-- Provide a quick summary of what the model is/does. --> | |
| 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 | |
| <!-- Provide a longer summary of what this model is. --> | |
| - **Developed by:** [Brain and Cognitive Science Club, IIT Kanpur](https://bcs-iitk.github.io/) | |