Instructions to use lightonai/RITA_s with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lightonai/RITA_s with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="lightonai/RITA_s", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("lightonai/RITA_s", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use lightonai/RITA_s with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "lightonai/RITA_s" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "lightonai/RITA_s", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/lightonai/RITA_s
- SGLang
How to use lightonai/RITA_s 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 "lightonai/RITA_s" \ --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": "lightonai/RITA_s", "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 "lightonai/RITA_s" \ --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": "lightonai/RITA_s", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use lightonai/RITA_s with Docker Model Runner:
docker model run hf.co/lightonai/RITA_s
File size: 650 Bytes
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"_name_or_path": "Seledorn/RITA_s",
"architectures": [
"RITAModelForCausalLM"
],
"auto_map": {
"AutoConfig": "rita_configuration.RITAConfig",
"AutoModel": "rita_modeling.RITAModel",
"AutoModelForCausalLM": "rita_modeling.RITAModelForCausalLM",
"AutoModelForSequenceClassification": "rita_modeling.RITAModelForSequenceClassification"
},
"d_feedforward": 3072,
"d_model": 768,
"dropout": 0.0,
"eos_token_id": 2,
"initializer_range": 0.02,
"max_seq_len": 1024,
"model_type": "rita",
"num_heads": 12,
"num_layers": 12,
"torch_dtype": "float16",
"transformers_version": "4.18.0",
"vocab_size": 26
}
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