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
File size: 759 Bytes
054df1d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | {
"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"
}
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