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Instructions to use AbteeXAILab/lumynax-tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AbteeXAILab/lumynax-tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="AbteeXAILab/lumynax-tiny")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AbteeXAILab/lumynax-tiny", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use AbteeXAILab/lumynax-tiny with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "AbteeXAILab/lumynax-tiny" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AbteeXAILab/lumynax-tiny", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/AbteeXAILab/lumynax-tiny
- SGLang
How to use AbteeXAILab/lumynax-tiny 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 "AbteeXAILab/lumynax-tiny" \ --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": "AbteeXAILab/lumynax-tiny", "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 "AbteeXAILab/lumynax-tiny" \ --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": "AbteeXAILab/lumynax-tiny", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use AbteeXAILab/lumynax-tiny with Docker Model Runner:
docker model run hf.co/AbteeXAILab/lumynax-tiny
File size: 825 Bytes
c0a10a9 | 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 | import sys
from pathlib import Path
from transformers import AutoModelForCausalLM, AutoTokenizer
if hasattr(sys.stdout, "reconfigure"):
sys.stdout.reconfigure(encoding="utf-8")
model_dir = Path(__file__).resolve().parent / "merged_model"
tokenizer = AutoTokenizer.from_pretrained(model_dir)
if tokenizer.pad_token is None:
tokenizer.pad_token = tokenizer.eos_token
model = AutoModelForCausalLM.from_pretrained(model_dir)
model.generation_config.temperature = None
model.generation_config.top_p = None
model.generation_config.top_k = None
encoded = tokenizer("Aotearoa is", return_tensors="pt")
output = model.generate(
**encoded,
max_new_tokens=48,
do_sample=False,
pad_token_id=tokenizer.eos_token_id,
)
print(tokenizer.decode(output[0], skip_special_tokens=True).strip())
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