Text Generation
Transformers
PyTorch
English
code
gpt_bigcode
starcoder
code_synthesis
competition-level_code_generation
text-generation-inference
Instructions to use flagopen/starcoder-15b-taco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use flagopen/starcoder-15b-taco with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="flagopen/starcoder-15b-taco")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("flagopen/starcoder-15b-taco") model = AutoModelForCausalLM.from_pretrained("flagopen/starcoder-15b-taco") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use flagopen/starcoder-15b-taco with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "flagopen/starcoder-15b-taco" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "flagopen/starcoder-15b-taco", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/flagopen/starcoder-15b-taco
- SGLang
How to use flagopen/starcoder-15b-taco 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 "flagopen/starcoder-15b-taco" \ --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": "flagopen/starcoder-15b-taco", "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 "flagopen/starcoder-15b-taco" \ --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": "flagopen/starcoder-15b-taco", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use flagopen/starcoder-15b-taco with Docker Model Runner:
docker model run hf.co/flagopen/starcoder-15b-taco
| { | |
| "add_bos_token": false, | |
| "add_prefix_space": false, | |
| "additional_special_tokens": [ | |
| "<|endoftext|>", | |
| "<fim_prefix>", | |
| "<fim_middle>", | |
| "<fim_suffix>", | |
| "<fim_pad>", | |
| "<filename>", | |
| "<gh_stars>", | |
| "<issue_start>", | |
| "<issue_comment>", | |
| "<issue_closed>", | |
| "<jupyter_start>", | |
| "<jupyter_text>", | |
| "<jupyter_code>", | |
| "<jupyter_output>", | |
| "<empty_output>", | |
| "<commit_before>", | |
| "<commit_msg>", | |
| "<commit_after>", | |
| "<reponame>" | |
| ], | |
| "bos_token": { | |
| "__type": "AddedToken", | |
| "content": "<|endoftext|>", | |
| "lstrip": false, | |
| "normalized": true, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "clean_up_tokenization_spaces": true, | |
| "eos_token": { | |
| "__type": "AddedToken", | |
| "content": "<|endoftext|>", | |
| "lstrip": false, | |
| "normalized": true, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "errors": "replace", | |
| "model_max_length": 2048, | |
| "pad_token": null, | |
| "padding_side": "right", | |
| "tokenizer_class": "GPT2Tokenizer", | |
| "unk_token": { | |
| "__type": "AddedToken", | |
| "content": "<|endoftext|>", | |
| "lstrip": false, | |
| "normalized": true, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "vocab_size": 49152 | |
| } | |