Text Generation
Transformers
PyTorch
Arabic
English
jais
Arabic
English
LLM
Decoder
causal-lm
custom_code
Instructions to use inceptionai/jais-13b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use inceptionai/jais-13b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="inceptionai/jais-13b", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("inceptionai/jais-13b", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use inceptionai/jais-13b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "inceptionai/jais-13b" # 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", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/inceptionai/jais-13b
- SGLang
How to use inceptionai/jais-13b 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" \ --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", "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" \ --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", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use inceptionai/jais-13b with Docker Model Runner:
docker model run hf.co/inceptionai/jais-13b
Update modeling_jais.py for compatibility with transformers
#20 opened 4 months ago
by
sylwia-kuros
add AIBOM
#19 opened 11 months ago
by
RiccardoDav
Adding `safetensors` variant of this model
#17 opened over 1 year ago
by
SFconvertbot
Adding `safetensors` variant of this model
#16 opened almost 2 years ago
by
SFconvertbot
Enabling PEFT for jais-13b
❤️ 2
#13 opened about 2 years ago
by
yassineafr
Adding `safetensors` variant of this model
#12 opened about 2 years ago
by
SFconvertbot
use core42/jais-13b with ollama
➕ 1
1
#11 opened over 2 years ago
by
akelmj
Running the model in Colab
2
#10 opened over 2 years ago
by
MohammadAlameenArtan
[AUTOMATED] Model Memory Requirements
#9 opened over 2 years ago
by
model-sizer-bot
The current model class (JAISModel) is not compatible with `.generate()`, as it doesn't have a language model head.
3
#8 opened over 2 years ago
by
FK7
Token limit
1
#6 opened over 2 years ago
by
alihkhawaher
training script
2
#5 opened over 2 years ago
by
maher13
any plan to release quantization that works with llama.cpp
👍 4
1
#3 opened over 2 years ago
by
ziyadalkhonein
JAIS model response takes a lot of time
4
#2 opened over 2 years ago
by
faris98