Text Generation
Transformers
ONNX
Safetensors
opt
trl
sft
optimum
danbooru
text-generation-inference
Instructions to use p1atdev/dart-v1-sft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use p1atdev/dart-v1-sft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="p1atdev/dart-v1-sft")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("p1atdev/dart-v1-sft") model = AutoModelForMultimodalLM.from_pretrained("p1atdev/dart-v1-sft") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use p1atdev/dart-v1-sft with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "p1atdev/dart-v1-sft" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "p1atdev/dart-v1-sft", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/p1atdev/dart-v1-sft
- SGLang
How to use p1atdev/dart-v1-sft 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 "p1atdev/dart-v1-sft" \ --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": "p1atdev/dart-v1-sft", "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 "p1atdev/dart-v1-sft" \ --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": "p1atdev/dart-v1-sft", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use p1atdev/dart-v1-sft with Docker Model Runner:
docker model run hf.co/p1atdev/dart-v1-sft
| { | |
| "one_external_file": true, | |
| "opset": null, | |
| "optimization": {}, | |
| "optimum_version": "1.17.1", | |
| "quantization": { | |
| "activations_dtype": "QUInt8", | |
| "activations_symmetric": false, | |
| "format": "QOperator", | |
| "is_static": false, | |
| "mode": "IntegerOps", | |
| "nodes_to_exclude": [], | |
| "nodes_to_quantize": [], | |
| "operators_to_quantize": [ | |
| "Conv", | |
| "MatMul", | |
| "Attention", | |
| "LSTM", | |
| "Gather", | |
| "Transpose", | |
| "EmbedLayerNormalization" | |
| ], | |
| "per_channel": false, | |
| "qdq_add_pair_to_weight": false, | |
| "qdq_dedicated_pair": false, | |
| "qdq_op_type_per_channel_support_to_axis": { | |
| "MatMul": 1 | |
| }, | |
| "reduce_range": false, | |
| "weights_dtype": "QInt8", | |
| "weights_symmetric": true | |
| }, | |
| "transformers_version": "4.37.2", | |
| "use_external_data_format": false | |
| } | |