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
README: decode with skip_special_tokens=True (EOS prefix is a doc boundary, not user text)
Browse files
README.md
CHANGED
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@@ -41,7 +41,7 @@ tokenizer = AutoTokenizer.from_pretrained(
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prompt = "The meaning of life is"
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inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
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out = model.generate(**inputs, effort="high", max_new_tokens=64)
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-
print(tokenizer.decode(out[0]))
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```
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With `pipeline`:
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prompt = "The meaning of life is"
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inputs = tokenizer(prompt, return_tensors="pt").to("cuda")
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out = model.generate(**inputs, effort="high", max_new_tokens=64)
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+
print(tokenizer.decode(out[0], skip_special_tokens=True))
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```
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With `pipeline`:
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