Instructions to use inceptionai/jais-30b-chat-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use inceptionai/jais-30b-chat-v3 with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="inceptionai/jais-30b-chat-v3", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("inceptionai/jais-30b-chat-v3", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use inceptionai/jais-30b-chat-v3 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "inceptionai/jais-30b-chat-v3"
# 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-30b-chat-v3",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/inceptionai/jais-30b-chat-v3

SGLang

How to use inceptionai/jais-30b-chat-v3 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-30b-chat-v3" \
    --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-30b-chat-v3",
		"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-30b-chat-v3" \
        --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-30b-chat-v3",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use inceptionai/jais-30b-chat-v3 with Docker Model Runner:
```
docker model run hf.co/inceptionai/jais-30b-chat-v3
```

Add Modeling for Jais Architecture to the Transformers repo

by beratcmn - opened Mar 20, 2024

Discussion

beratcmn

Mar 20, 2024

Adding modelling for Jais similar to LLama models (https://github.com/huggingface/transformers/blob/main/src/transformers/models/llama/modeling_llama.py) would be very beneficial for custom engine integrations. By adding a modelling we can use engines such as VLLM and Text Generation Inference much more efficiently.

beratcmn changed discussion title from Add Modeling for Jais Architecture to Add Modeling for Jais Architecture to the Transformers repo Mar 20, 2024

grandiose-pizza

Inception org Mar 23, 2024

It is in plans. Will update next month.

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment