Text Generation
Transformers
Safetensors
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text-generation-inference
Eval Results (legacy)
Instructions to use Polygl0t/LilTii-v0.2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Polygl0t/LilTii-v0.2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Polygl0t/LilTii-v0.2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Polygl0t/LilTii-v0.2") model = AutoModelForCausalLM.from_pretrained("Polygl0t/LilTii-v0.2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Polygl0t/LilTii-v0.2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Polygl0t/LilTii-v0.2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Polygl0t/LilTii-v0.2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Polygl0t/LilTii-v0.2
- SGLang
How to use Polygl0t/LilTii-v0.2 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/LilTii-v0.2" \ --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/LilTii-v0.2", "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/LilTii-v0.2" \ --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/LilTii-v0.2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Polygl0t/LilTii-v0.2 with Docker Model Runner:
docker model run hf.co/Polygl0t/LilTii-v0.2
Download learning_curves.png from Polygl0t/LilTii-v0.2: direct link, hf CLI and curl.
- Browser
- Download file 361 kB
-
https://huggingface.co/Polygl0t/LilTii-v0.2/resolve/adf1d1787c88fa07869852f473f7972882428765/learning_curves.png
- Command line
-
hf download hf://Polygl0t/LilTii-v0.2@adf1d1787c88fa07869852f473f7972882428765/learning_curves.png
-
curl -L -o learning_curves.png https://huggingface.co/Polygl0t/LilTii-v0.2/resolve/adf1d1787c88fa07869852f473f7972882428765/learning_curves.png
361 kB

- Xet hash:
- a9118b9da34ae6b3fe9c327b9a1c9ca9e494f9bed438e78922f7b33e98fd87ce
- Size of remote file:
- 361 kB
- SHA256:
- 209176ab393200356da462e608242a77c3fe6e119d3b2e19941992c46a1fc6a1
·
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