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

File size: 1,624 Bytes

313931e

{
  "architectures": [
    "IQuestQ1ForCausalLM"
  ],
  "attention_bias": false,
  "attention_dropout": 0.0,
  "attn_out_scale": 1.0,
  "dense_intermediate_size": 12288,
  "dtype": "bfloat16",
  "embed_scale": 1.0,
  "enable_sink_attention": true,
  "eos_token_id": 0,
  "ffn_out_scale": 0.53881590608,
  "first_layer_attn_out_scale": 1.0,
  "first_layer_ffn_out_scale": 1.0,
  "first_layers_types": [
    "full_attention"
  ],
  "fuse_sink_attention": true,
  "head_dim": 128,
  "hidden_act": "silu",
  "hidden_size": 3072,
  "hybrid_layers_types_block": [
    "full_attention",
    "sliding_attention",
    "sliding_attention",
    "sliding_attention"
  ],
  "intermediate_size": 1536,
  "last_layers_types": [
    "full_attention",
    "full_attention",
    "full_attention"
  ],
  "logit_scale": 1.0,
  "max_position_embeddings": 524288,
  "mlp_only_layers": [
    0
  ],
  "model_type": "iquest_q1",
  "moe_router_dtype": "fp32",
  "enable_lm_head_fp32": true,
  "no_rope_layers": [],
  "num_attention_heads": 48,
  "num_experts": 256,
  "num_experts_per_tok": 8,
  "num_hidden_layers": 88,
  "num_hybrid_layers_block": 21,
  "num_key_value_heads": 8,
  "num_mtp_layers": 0,
  "rms_norm_eps": 1e-06,
  "rope_theta": 1000000,
  "rotary_dim": 32,
  "shared_kv_num_layers": 0,
  "shared_kv_source_begin": 0,
  "shared_kv_target_begin": 0,
  "sliding_window": 4096,
  "softmax_scale": null,
  "swa_rope_theta": 10000.0,
  "tie_word_embeddings": false,
  "transformers_version": "4.57.1",
  "use_cache": true,
  "use_hybrid_layers": true,
  "use_over_encoding": false,
  "use_sliding_window": true,
  "vocab_size": 160000
}