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
starcoder uses Megatron-LM?
Software Orchestration: Megatron-LM
But from code like class GPTBigCodeBlock doesn't use megatron.
anything wrong?
@senxiangms checkout the pre-training code at https://github.com/bigcode-project/Megatron-LM.
ic. appreciated.
@senxiangms checkout the pre-training code at https://github.com/bigcode-project/Megatron-LM.
should I look at Megatron-LM/examples/pretrain_bigcode_model.slurm as entry point?
Thanks.
The pre-training was done in Megatron-LM and then we converted the checkpoints to transformers which uses GPTBigCodeBlock ... If you're looking for the code to train the model in Megatron-LM it's there and the slurm script to launch the job is indeed Megatron-LM/examples/pretrain_bigcode_model.slurm but it's specific to our cluster otherwise you can just use transformers
Thanks, @loubnabnl . well explained.
@loubnabnl , where can I find the original megatron-LM pretrained starcoder checkpoint instead of the converted one published in hugging face hub.
Thanks.
How to converted the checkpoints to transformers?
How to converted the checkpoints to
transformers?
Do you solve it?