Instructions to use IQuestLab/IQuest-Q1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use IQuestLab/IQuest-Q1 with Transformers:

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

pipe = pipeline("text-generation", model="IQuestLab/IQuest-Q1")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("IQuestLab/IQuest-Q1", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use IQuestLab/IQuest-Q1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "IQuestLab/IQuest-Q1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "IQuestLab/IQuest-Q1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/IQuestLab/IQuest-Q1

SGLang

How to use IQuestLab/IQuest-Q1 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 "IQuestLab/IQuest-Q1" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "IQuestLab/IQuest-Q1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "IQuestLab/IQuest-Q1" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "IQuestLab/IQuest-Q1",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use IQuestLab/IQuest-Q1 with Docker Model Runner:
```
docker model run hf.co/IQuestLab/IQuest-Q1
```

IQuest-Q1

Commit History

Update License and metadata

6539c7f
verified

zwpride-iquestlab commited on 13 days ago

Submission of the initial version of IQuest-Q1 (#1)

8bfc391

yunyin007

zwpride-iquestlab commited on 13 days ago

Upload folder using huggingface_hub

7153c58
verified

yunyin007 commited on 13 days ago

Upload folder using huggingface_hub

313931e
verified

yunyin007 commited on 13 days ago

initial commit

dc8655f
verified

yunyin007 commited on 13 days ago

Commit History

Update License and metadata 6539c7f verified

Submission of the initial version of IQuest-Q1 (#1) 8bfc391

Upload folder using huggingface_hub 7153c58 verified

Upload folder using huggingface_hub 313931e verified

initial commit dc8655f verified

Update License and metadata

6539c7f
verified

Submission of the initial version of IQuest-Q1 (#1)

8bfc391

Upload folder using huggingface_hub

7153c58
verified

Upload folder using huggingface_hub

313931e
verified

initial commit

dc8655f
verified