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
```

VLLM is not supporting JAISLMHeadModel

by MayaBsat02 - opened Mar 28, 2024

Discussion

MayaBsat02

Mar 28, 2024

ValueError: Model architectures ['JAISLMHeadModel'] are not supported for now. Supported architectures: ['AquilaModel', 'AquilaForCausalLM', 'BaiChuanForCausalLM', 'BaichuanForCausalLM', 'BloomForCausalLM', 'ChatGLMModel', 'ChatGLMForConditionalGeneration', 'DeciLMForCausalLM', 'DeepseekForCausalLM', 'FalconForCausalLM', 'GemmaForCausalLM', 'GPT2LMHeadModel', 'GPTBigCodeForCausalLM', 'GPTJForCausalLM', 'GPTNeoXForCausalLM', 'InternLMForCausalLM', 'InternLM2ForCausalLM', 'LlamaForCausalLM', 'LLaMAForCausalLM', 'MistralForCausalLM', 'MixtralForCausalLM', 'QuantMixtralForCausalLM', 'MptForCausalLM', 'MPTForCausalLM', 'OLMoForCausalLM', 'OPTForCausalLM', 'OrionForCausalLM', 'PhiForCausalLM', 'QWenLMHeadModel', 'Qwen2ForCausalLM', 'RWForCausalLM', 'StableLMEpochForCausalLM', 'StableLmForCausalLM', 'Starcoder2ForCausalLM']

grandiose-pizza

Inception org Mar 28, 2024

Hi, have you installed vLLM via pip or build from source using the latest main? Also please use the parameter trust_remote_code=True or --trust-remote-code for engine/ api respectively.

alielfilali01 changed discussion status to closed Jan 2, 2025

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