Instructions to use inceptionai/jais-13b-chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use inceptionai/jais-13b-chat with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="inceptionai/jais-13b-chat", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("inceptionai/jais-13b-chat", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use inceptionai/jais-13b-chat with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "inceptionai/jais-13b-chat" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "inceptionai/jais-13b-chat", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/inceptionai/jais-13b-chat
- SGLang
How to use inceptionai/jais-13b-chat 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 "inceptionai/jais-13b-chat" \ --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": "inceptionai/jais-13b-chat", "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 "inceptionai/jais-13b-chat" \ --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": "inceptionai/jais-13b-chat", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use inceptionai/jais-13b-chat with Docker Model Runner:
docker model run hf.co/inceptionai/jais-13b-chat
Quantized Versions of jais-13b-chat
Hello,
I'm using the "jais-13b-chat" model and find it beneficial. For optimization purposes, could you consider providing 4-bit and 8-bit quantized versions? This would greatly assist deployments in resource-limited environments.
Thanks for considering,
Noureddine
you can use bitsandbytes directly on jais
There is this quantized version (https://huggingface.co/mouaff25/jais-13b-chat-8bit) but it did not work for me. Model loaded by got tensor mismatch error.
There is this quantized version (https://huggingface.co/mouaff25/jais-13b-chat-8bit) but it did not work for me. Model loaded by got tensor mismatch error.
It works using A100 :
https://colab.research.google.com/drive/1QLihIVHOnWrz5P7XER4mn13YuGAbnPDq?usp=sharing
I've just pushed an 8-bit quantized version , feel free to check it 'drakkola/jais-13b-chat-8bit'