Text Generation
Transformers
PyTorch
code
gpt2
custom_code
Eval Results (legacy)
text-generation-inference
Instructions to use bigcode/santacoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bigcode/santacoder with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="bigcode/santacoder", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("bigcode/santacoder", trust_remote_code=True) model = AutoModelForCausalLM.from_pretrained("bigcode/santacoder", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use bigcode/santacoder with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "bigcode/santacoder" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "bigcode/santacoder", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/bigcode/santacoder
- SGLang
How to use bigcode/santacoder 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/santacoder" \ --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/santacoder", "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/santacoder" \ --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/santacoder", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use bigcode/santacoder with Docker Model Runner:
docker model run hf.co/bigcode/santacoder
max_length_generation
#32
by kcdharma - opened
Hi,
I am trying to reproduce santacoder on humaneval, what value of max_length_generation did you guys use? Thank you.
Also, what value of temperature did you use? Thank you.
For pass@100, here's the execution command in bigcode evaluation harness (for pass@1 use temperature 0.2)
accelerate launch main.py \
--model bigcode/santacoder \
--max_length_generation 512 \
--tasks humaneval \
--n_samples 200 \
--batch_size 200 \
--temperature 0.8 \
--allow_code_execution \
--trust_remote_code
The reported number is the HumanEval version of MultiPL-E to run it you can replace humaneval with multiple-py
Thank you @loubnabnl
loubnabnl changed discussion status to closed