Text Generation
Transformers
PyTorch
Safetensors
gpt_bigcode
code
Eval Results (legacy)
text-generation-inference
Instructions to use bigcode/starcoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bigcode/starcoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="bigcode/starcoder")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("bigcode/starcoder") model = AutoModelForCausalLM.from_pretrained("bigcode/starcoder") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use bigcode/starcoder with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bigcode/starcoder" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "bigcode/starcoder", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/bigcode/starcoder
- SGLang
How to use bigcode/starcoder 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 "bigcode/starcoder" \ --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": "bigcode/starcoder", "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 "bigcode/starcoder" \ --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": "bigcode/starcoder", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use bigcode/starcoder with Docker Model Runner:
docker model run hf.co/bigcode/starcoder
Stopping criteria
#94
by AnudeepPeela - opened
Hello,
Any references on how to implement stopping criteria for the starcoder model?
Thanks in advance!
This comment has been hidden
In case it helps, I wrote one for stop-sequences, similar to OpenAI usage. Could probably be done faster/more cleverly, but for large LLMs where each forward is the bottleneck, it's saved plenty of time by allowing for early termination. Also wrote in some utilities for extracting the completion up to the stop-sequence and it's log-probabilities, as this was neede for my use-case.