Instructions to use ProCreations/Booper-Big with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ProCreations/Booper-Big with Transformers:

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

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

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ProCreations/Booper-Big")
model = AutoModelForCausalLM.from_pretrained("ProCreations/Booper-Big", device_map="auto")
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=256)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ProCreations/Booper-Big with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/ProCreations/Booper-Big

SGLang

How to use ProCreations/Booper-Big 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 "ProCreations/Booper-Big" \
    --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": "ProCreations/Booper-Big",
		"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 "ProCreations/Booper-Big" \
        --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": "ProCreations/Booper-Big",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use ProCreations/Booper-Big with Docker Model Runner:
```
docker model run hf.co/ProCreations/Booper-Big
```

Booper-Big

File size: 798 Bytes

ba40e5d

{
  "active_parameters_per_token": 50512000,
  "architecture": {
    "hidden_size": 896,
    "intermediate_size": 1024,
    "max_position_embeddings": 4096,
    "num_attention_heads": 14,
    "num_experts_per_tok": 1,
    "num_hidden_layers": 6,
    "num_key_value_heads": 14,
    "num_local_experts": 7,
    "vocab_size": 16384
  },
  "assistant_target_tokens": null,
  "completed_budget": true,
  "context_window": 4096,
  "dataset": "openbmb/Ultra-FineWeb (en, score>=0.70)",
  "elapsed_seconds": 14777.457427978516,
  "finished_at": "2026-08-26T07:11:20Z",
  "precision": "bf16 autocast with fp32 master weights",
  "qat": false,
  "qat_scheme": null,
  "sequence_length_trained": 1024,
  "stage": "pretrain",
  "steps": 50863,
  "tokens_trained": 5000036352,
  "total_parameters": 149602432
}