Instructions to use aimeri/spoomplesmaxx-v2-30B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use aimeri/spoomplesmaxx-v2-30B with Transformers:

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

pipe = pipeline("text-generation", model="aimeri/spoomplesmaxx-v2-30B")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("aimeri/spoomplesmaxx-v2-30B")
model = AutoModelForCausalLM.from_pretrained("aimeri/spoomplesmaxx-v2-30B")
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 aimeri/spoomplesmaxx-v2-30B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "aimeri/spoomplesmaxx-v2-30B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "aimeri/spoomplesmaxx-v2-30B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/aimeri/spoomplesmaxx-v2-30B

SGLang

How to use aimeri/spoomplesmaxx-v2-30B 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 "aimeri/spoomplesmaxx-v2-30B" \
    --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": "aimeri/spoomplesmaxx-v2-30B",
		"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 "aimeri/spoomplesmaxx-v2-30B" \
        --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": "aimeri/spoomplesmaxx-v2-30B",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use aimeri/spoomplesmaxx-v2-30B with Docker Model Runner:
```
docker model run hf.co/aimeri/spoomplesmaxx-v2-30B
```

spoomplesmaxx-v2-30B / adapter_config.json

aimeri

Upload model trained with Unsloth

ac13f3e verified about 1 month ago

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	{
	"alora_invocation_tokens": null,
	"alpha_pattern": {},
	"arrow_config": null,
	"auto_mapping": {
	"base_model_class": "GraniteForCausalLM",
	"parent_library": "transformers.models.granite.modeling_granite",
	"unsloth_fixed": true
	},
	"base_model_name_or_path": "ibm-granite/granite-4.1-30b-base",
	"bias": "none",
	"corda_config": null,
	"ensure_weight_tying": false,
	"eva_config": null,
	"exclude_modules": null,
	"fan_in_fan_out": false,
	"inference_mode": true,
	"init_lora_weights": true,
	"layer_replication": null,
	"layers_pattern": null,
	"layers_to_transform": null,
	"loftq_config": {},
	"lora_alpha": 64,
	"lora_bias": false,
	"lora_dropout": 0,
	"lora_ga_config": null,
	"megatron_config": null,
	"megatron_core": "megatron.core",
	"modules_to_save": null,
	"peft_type": "LORA",
	"peft_version": "0.19.1",
	"qalora_group_size": 16,
	"r": 64,
	"rank_pattern": {},
	"revision": null,
	"target_modules": "(?:.?(?:vision\|image\|visual\|patch\|language\|text).?(?:self_attn\|attention\|attn\|mlp\|feed_forward\|ffn\|dense).?(?:q_proj\|k_proj\|v_proj\|o_proj\|gate_proj\|up_proj\|down_proj).?)\|(?:\\bmodel\\.layers\\.[\\d]{1,}\\.(?:self_attn\|attention\|attn\|mlp\|feed_forward\|ffn\|dense)\\.(?:(?:q_proj\|k_proj\|v_proj\|o_proj\|gate_proj\|up_proj\|down_proj)))",
	"target_parameters": null,
	"task_type": "CAUSAL_LM",
	"trainable_token_indices": null,
	"use_bdlora": null,
	"use_dora": false,
	"use_qalora": false,
	"use_rslora": false
	}