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
Upload folder using huggingface_hub
Browse files- README.md +2 -0
- charts/banner.svg +4 -0
README.md
CHANGED
|
@@ -10,6 +10,8 @@ tags:
|
|
| 10 |
- sub-10m
|
| 11 |
---
|
| 12 |
|
|
|
|
|
|
|
| 13 |
# min-spark
|
| 14 |
|
| 15 |
**min-spark is a 5.76M-parameter language model with native effort levels.** It introduces controllable depth to the sub-10M model class. The same checkpoint can produce a quick completion or spend more computation on the same prompt, selected with one inference argument.
|
|
|
|
| 10 |
- sub-10m
|
| 11 |
---
|
| 12 |
|
| 13 |
+

|
| 14 |
+
|
| 15 |
# min-spark
|
| 16 |
|
| 17 |
**min-spark is a 5.76M-parameter language model with native effort levels.** It introduces controllable depth to the sub-10M model class. The same checkpoint can produce a quick completion or spend more computation on the same prompt, selected with one inference argument.
|
charts/banner.svg
ADDED
|
|