Instructions to use rovai/AI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rovai/AI with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="rovai/AI")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("rovai/AI") model = AutoModelForCausalLM.from_pretrained("rovai/AI", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use rovai/AI with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "rovai/AI" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rovai/AI", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/rovai/AI
- SGLang
How to use rovai/AI 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 "rovai/AI" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rovai/AI", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "rovai/AI" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rovai/AI", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use rovai/AI with Docker Model Runner:
docker model run hf.co/rovai/AI
Download pytorch_model.bin from rovai/AI: direct link, hf CLI and curl.
- Browser
- Download file 1.44 GB
-
https://huggingface.co/rovai/AI/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://rovai/AI/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/rovai/AI/resolve/main/pytorch_model.bin
1.44 GB
- Xet hash:
- 48715d024206683ce39625edec403ab1b9cb50253f4627a139aacaa62e36af7d
- Size of remote file:
- 1.44 GB
- SHA256:
- 64896da155e7fd2e262423c73f9aef5b7f94cebf0a89eeea62775baacc76af1e
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