Text Generation
Transformers
Safetensors
minspark
language-model
transformer
rope
gqa
custom_code
tiny
looped
slm
custom-architecture
custom-tokenizer
Instructions to use MinimaLabs/min-spark with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MinimaLabs/min-spark with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="MinimaLabs/min-spark", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("MinimaLabs/min-spark", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use MinimaLabs/min-spark with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "MinimaLabs/min-spark" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "MinimaLabs/min-spark", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/MinimaLabs/min-spark
- SGLang
How to use MinimaLabs/min-spark 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 "MinimaLabs/min-spark" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "MinimaLabs/min-spark", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "MinimaLabs/min-spark" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "MinimaLabs/min-spark", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use MinimaLabs/min-spark with Docker Model Runner:
docker model run hf.co/MinimaLabs/min-spark
| { | |
| "architectures": ["MinSparkForCausalLM"], | |
| "model_type": "minspark", | |
| "pipeline_tag": "text-generation", | |
| "auto_map": { | |
| "AutoConfig": "configuration_minspark.MinSparkConfig", | |
| "AutoModelForCausalLM": "modeling_minspark.MinSparkForCausalLM" | |
| }, | |
| "vocab_size": 4096, | |
| "dim": 288, | |
| "n_heads": 6, | |
| "n_kv_heads": 2, | |
| "ffn_hidden": 768, | |
| "prelude_layers": 1, | |
| "coda_layers": 1, | |
| "body_blocks": 3, | |
| "max_loops": 4, | |
| "train_loops": 3, | |
| "lora_rank": 16, | |
| "rope_base": 10000.0, | |
| "max_seq_len": 512, | |
| "max_position_embeddings": 512, | |
| "ddl_beta_init": 1.0, | |
| "ddl_k_eps": 0.01, | |
| "ddl_v_sigmoid_scale": 4.0, | |
| "doc_mask_eos": 2, | |
| "effort": "medium", | |
| "use_cache": false, | |
| "tie_word_embeddings": true, | |
| "transformers_version": "5.14.1" | |
| } | |