Instructions to use NumbersStation/nsql-350M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NumbersStation/nsql-350M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="NumbersStation/nsql-350M")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("NumbersStation/nsql-350M") model = AutoModelForCausalLM.from_pretrained("NumbersStation/nsql-350M") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use NumbersStation/nsql-350M with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "NumbersStation/nsql-350M" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "NumbersStation/nsql-350M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/NumbersStation/nsql-350M
- SGLang
How to use NumbersStation/nsql-350M 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 "NumbersStation/nsql-350M" \ --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": "NumbersStation/nsql-350M", "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 "NumbersStation/nsql-350M" \ --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": "NumbersStation/nsql-350M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use NumbersStation/nsql-350M with Docker Model Runner:
docker model run hf.co/NumbersStation/nsql-350M
Predefined Model maximum length exceeded
#8
by kamil - opened
Hello,
Thank you for sharing this great model.
I am facing the following issue: This is a friendly reminder - the current text generation call will exceed the model's predefined maximum length (2048). Depending on the model, you may observe exceptions, performance degradation, or nothing at all.
Is there any way to increase this limit ?
Thank you