Instructions to use DarianNLP/no_schema_tiny_sql with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DarianNLP/no_schema_tiny_sql with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="DarianNLP/no_schema_tiny_sql")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("DarianNLP/no_schema_tiny_sql") model = AutoModelForCausalLM.from_pretrained("DarianNLP/no_schema_tiny_sql") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use DarianNLP/no_schema_tiny_sql with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "DarianNLP/no_schema_tiny_sql" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "DarianNLP/no_schema_tiny_sql", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/DarianNLP/no_schema_tiny_sql
- SGLang
How to use DarianNLP/no_schema_tiny_sql 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 "DarianNLP/no_schema_tiny_sql" \ --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": "DarianNLP/no_schema_tiny_sql", "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 "DarianNLP/no_schema_tiny_sql" \ --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": "DarianNLP/no_schema_tiny_sql", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use DarianNLP/no_schema_tiny_sql with Docker Model Runner:
docker model run hf.co/DarianNLP/no_schema_tiny_sql
| { | |
| "activation_function": "gelu_new", | |
| "architectures": [ | |
| "GPTNeoForCausalLM" | |
| ], | |
| "attention_dropout": 0, | |
| "attention_layers": [ | |
| "global", | |
| "local", | |
| "global", | |
| "local" | |
| ], | |
| "attention_types": [ | |
| [ | |
| [ | |
| "global", | |
| "local" | |
| ], | |
| 2 | |
| ] | |
| ], | |
| "bos_token_id": 50256, | |
| "classifier_dropout": 0.1, | |
| "dtype": "float32", | |
| "embed_dropout": 0, | |
| "eos_token_id": 50256, | |
| "gradient_checkpointing": false, | |
| "hidden_size": 768, | |
| "initializer_range": 0.02, | |
| "intermediate_size": null, | |
| "layer_norm_epsilon": 1e-05, | |
| "max_position_embeddings": 2048, | |
| "model_type": "gpt_neo", | |
| "num_heads": 16, | |
| "num_layers": 4, | |
| "pad_token_id": 50256, | |
| "resid_dropout": 0, | |
| "summary_activation": null, | |
| "summary_first_dropout": 0.1, | |
| "summary_proj_to_labels": true, | |
| "summary_type": "cls_index", | |
| "summary_use_proj": true, | |
| "transformers_version": "4.57.6", | |
| "use_cache": true, | |
| "vocab_size": 50257, | |
| "window_size": 256 | |
| } | |