Text Generation
Transformers
Safetensors
Hindi
llama
text-generation-inference
Eval Results (legacy)
Instructions to use Polygl0t/LilMoo-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Polygl0t/LilMoo-v0.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Polygl0t/LilMoo-v0.1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Polygl0t/LilMoo-v0.1") model = AutoModelForCausalLM.from_pretrained("Polygl0t/LilMoo-v0.1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Polygl0t/LilMoo-v0.1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Polygl0t/LilMoo-v0.1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Polygl0t/LilMoo-v0.1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Polygl0t/LilMoo-v0.1
- SGLang
How to use Polygl0t/LilMoo-v0.1 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 "Polygl0t/LilMoo-v0.1" \ --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": "Polygl0t/LilMoo-v0.1", "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 "Polygl0t/LilMoo-v0.1" \ --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": "Polygl0t/LilMoo-v0.1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Polygl0t/LilMoo-v0.1 with Docker Model Runner:
docker model run hf.co/Polygl0t/LilMoo-v0.1
Download plots/arc.png from Polygl0t/LilMoo-v0.1: direct link, hf CLI and curl.
- Browser
- Download file 136 kB
-
https://huggingface.co/Polygl0t/LilMoo-v0.1/resolve/main/plots/arc.png
- Command line
-
hf download hf://Polygl0t/LilMoo-v0.1/plots/arc.png
-
curl -L -o arc.png https://huggingface.co/Polygl0t/LilMoo-v0.1/resolve/main/plots/arc.png
136 kB

- Xet hash:
- b2b3caf4870bee6b62b6fd08f2d4aac152f7464a56b0b9377769dee864ec8fcc
- Size of remote file:
- 136 kB
- SHA256:
- 55a43fd07bd95cc3d46ca51ef9c84dfe114870702ed471739f8ec1c0f721a563
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