Instructions to use namuai-x/MapleTree-1.0-8B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use namuai-x/MapleTree-1.0-8B with Transformers:

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

pipe = pipeline("text-generation", model="namuai-x/MapleTree-1.0-8B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("namuai-x/MapleTree-1.0-8B")
model = AutoModelForMultimodalLM.from_pretrained("namuai-x/MapleTree-1.0-8B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use namuai-x/MapleTree-1.0-8B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "namuai-x/MapleTree-1.0-8B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "namuai-x/MapleTree-1.0-8B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/namuai-x/MapleTree-1.0-8B

SGLang

How to use namuai-x/MapleTree-1.0-8B 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 "namuai-x/MapleTree-1.0-8B" \
    --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": "namuai-x/MapleTree-1.0-8B",
		"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 "namuai-x/MapleTree-1.0-8B" \
        --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": "namuai-x/MapleTree-1.0-8B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use namuai-x/MapleTree-1.0-8B with Docker Model Runner:
```
docker model run hf.co/namuai-x/MapleTree-1.0-8B
```

MapleTree-1.0-8B / args.json

namuai-x

MapleTree-1.0-8B initial release

8a3df50 1 day ago

raw

history blame contribute delete

6.42 kB

	{
	"model": "/dataset/tim/model/LLM_base/Qwen3-8B-Base",
	"model_type": "qwen3",
	"model_revision": null,
	"task_type": "causal_lm",
	"torch_dtype": "bfloat16",
	"attn_impl": null,
	"num_labels": null,
	"problem_type": null,
	"rope_scaling": null,
	"device_map": null,
	"max_memory": {},
	"local_repo_path": null,
	"init_strategy": null,
	"template": "qwen3",
	"system": null,
	"max_length": 2048,
	"truncation_strategy": "delete",
	"max_pixels": null,
	"agent_template": null,
	"norm_bbox": null,
	"use_chat_template": true,
	"padding_free": false,
	"padding_side": "right",
	"loss_scale": "default",
	"sequence_parallel_size": 1,
	"response_prefix": null,
	"template_backend": "swift",
	"dataset": [],
	"val_dataset": [],
	"split_dataset_ratio": 0.01,
	"data_seed": 42,
	"dataset_num_proc": 1,
	"load_from_cache_file": true,
	"dataset_shuffle": true,
	"val_dataset_shuffle": false,
	"streaming": false,
	"interleave_prob": null,
	"stopping_strategy": "first_exhausted",
	"shuffle_buffer_size": 1000,
	"download_mode": "reuse_dataset_if_exists",
	"columns": {},
	"strict": false,
	"remove_unused_columns": true,
	"model_name": null,
	"model_author": null,
	"custom_dataset_info": [],
	"quant_method": null,
	"quant_bits": null,
	"hqq_axis": null,
	"bnb_4bit_compute_dtype": "bfloat16",
	"bnb_4bit_quant_type": "nf4",
	"bnb_4bit_use_double_quant": true,
	"bnb_4bit_quant_storage": null,
	"max_new_tokens": null,
	"temperature": null,
	"top_k": null,
	"top_p": null,
	"repetition_penalty": null,
	"num_beams": 1,
	"stream": false,
	"stop_words": [],
	"logprobs": false,
	"top_logprobs": null,
	"ckpt_dir": null,
	"lora_modules": [],
	"tuner_backend": "peft",
	"train_type": "lora",
	"adapters": [],
	"external_plugins": [],
	"seed": 42,
	"model_kwargs": {},
	"load_args": true,
	"load_data_args": false,
	"packing": false,
	"packing_cache": null,
	"custom_register_path": [],
	"use_hf": false,
	"hub_token": null,
	"ddp_timeout": 18000000,
	"ddp_backend": null,
	"ignore_args_error": false,
	"use_swift_lora": false,
	"merge_lora": false,
	"safe_serialization": true,
	"max_shard_size": "5GB",
	"output_dir": "/dataset/tim/output/megatron2hf/NamuAI_8b_wpml_v0.8.0_iter_0090586_hf",
	"quant_n_samples": 256,
	"quant_batch_size": 1,
	"group_size": 128,
	"to_ollama": false,
	"to_mcore": false,
	"to_hf": true,
	"mcore_model": "/dataset/tim/output/megatron-swift/qwen3_8b_8192_tp2_dp2_wpml6000_v080_train/sft/v1-20260530-173549",
	"thread_count": 2,
	"test_convert_precision": false,
	"push_to_hub": false,
	"hub_model_id": null,
	"hub_private_repo": false,
	"commit_message": "update files",
	"to_peft_format": false,
	"exist_ok": false,
	"rank": 0,
	"local_rank": 0,
	"global_world_size": 1,
	"local_world_size": 1,
	"model_suffix": "Qwen3-8B-Base",
	"model_info": "ModelInfo(model_type='qwen3', model_dir='/dataset/tim/model/LLM_base/Qwen3-8B-Base', torch_dtype=torch.bfloat16, max_model_len=32768, quant_method=None, quant_bits=None, rope_scaling=None, config=None, task_type='causal_lm', num_labels=None)",
	"model_meta": "ModelMeta(model_type='qwen3', model_groups=[ModelGroup(models=[Model(ms_model_id='Qwen/Qwen3-0.6B-Base', hf_model_id='Qwen/Qwen3-0.6B-Base', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-1.7B-Base', hf_model_id='Qwen/Qwen3-1.7B-Base', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-4B-Base', hf_model_id='Qwen/Qwen3-4B-Base', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-8B-Base', hf_model_id='Qwen/Qwen3-8B-Base', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-14B-Base', hf_model_id='Qwen/Qwen3-14B-Base', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-0.6B', hf_model_id='Qwen/Qwen3-0.6B', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-1.7B', hf_model_id='Qwen/Qwen3-1.7B', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-4B', hf_model_id='Qwen/Qwen3-4B', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-8B', hf_model_id='Qwen/Qwen3-8B', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-14B', hf_model_id='Qwen/Qwen3-14B', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-32B', hf_model_id='Qwen/Qwen3-32B', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-0.6B-FP8', hf_model_id='Qwen/Qwen3-0.6B-FP8', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-1.7B-FP8', hf_model_id='Qwen/Qwen3-1.7B-FP8', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-4B-FP8', hf_model_id='Qwen/Qwen3-4B-FP8', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-8B-FP8', hf_model_id='Qwen/Qwen3-8B-FP8', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-14B-FP8', hf_model_id='Qwen/Qwen3-14B-FP8', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-32B-FP8', hf_model_id='Qwen/Qwen3-32B-FP8', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-4B-AWQ', hf_model_id='Qwen/Qwen3-4B-AWQ', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-8B-AWQ', hf_model_id='Qwen/Qwen3-8B-AWQ', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-14B-AWQ', hf_model_id='Qwen/Qwen3-14B-AWQ', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='Qwen/Qwen3-32B-AWQ', hf_model_id='Qwen/Qwen3-32B-AWQ', model_path=None, ms_revision=None, hf_revision=None), Model(ms_model_id='swift/Qwen3-32B-AWQ', hf_model_id=None, model_path=None, ms_revision=None, hf_revision=None)], ignore_patterns=None, requires=None, tags=[])], template='qwen3', get_function=<function get_model_tokenizer_with_flash_attn at 0x7fbdb3644160>, model_arch='llama', architectures=['Qwen3ForCausalLM'], additional_saved_files=[], torch_dtype=None, is_multimodal=False, is_reward=False, task_type=None, ignore_patterns=None, requires=['transformers>=4.51'], tags=[])",
	"model_dir": "/dataset/tim/model/LLM_base/Qwen3-8B-Base",
	"hub": "<class 'swift.hub.hub.MSHub'>"
	}