Instructions to use inception42/jais-30b-chat-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use inception42/jais-30b-chat-v1 with Transformers:

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

pipe = pipeline("text-generation", model="inception42/jais-30b-chat-v1", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("inception42/jais-30b-chat-v1", trust_remote_code=True, device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use inception42/jais-30b-chat-v1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "inception42/jais-30b-chat-v1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "inception42/jais-30b-chat-v1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/inception42/jais-30b-chat-v1

SGLang

How to use inception42/jais-30b-chat-v1 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 "inception42/jais-30b-chat-v1" \
    --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": "inception42/jais-30b-chat-v1",
		"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 "inception42/jais-30b-chat-v1" \
        --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": "inception42/jais-30b-chat-v1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use inception42/jais-30b-chat-v1 with Docker Model Runner:
```
docker model run hf.co/inception42/jais-30b-chat-v1
```

issue about evaluate script

by hh2017 - opened Dec 11, 2023

Discussion

hh2017

Dec 11, 2023

Hello,

Firstly, I want to extend my gratitude for your incredible work in the field of open-source NLP. Your contributions have been invaluable to the community.

I am reaching out to inquire if you could provide the zero-shot script used for testing the Jais-30B-chat model on MMLU-like Arabic datasets. I've been attempting to use the model for multiple-choice questions, but unfortunately, my attempts result in responses such as, "I'm sorry, I cannot provide the correct answer to multiple-choice questions. " For reference, I am using the 'prompt_ar' provided on your hf platform.

Additionally, I have another question regarding benchmark assessments for multiple-choice questions. When you conduct these benchmark evaluations, is the 'config' also set with 'do_sample=true'?

Any guidance or information you can provide would be greatly appreciated.

Best regards,

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