Instructions to use AISE-TUDelft/CodeGPT-Multilingual with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AISE-TUDelft/CodeGPT-Multilingual with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="AISE-TUDelft/CodeGPT-Multilingual", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("AISE-TUDelft/CodeGPT-Multilingual") model = AutoModelForCausalLM.from_pretrained("AISE-TUDelft/CodeGPT-Multilingual", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use AISE-TUDelft/CodeGPT-Multilingual with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "AISE-TUDelft/CodeGPT-Multilingual" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AISE-TUDelft/CodeGPT-Multilingual", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/AISE-TUDelft/CodeGPT-Multilingual
- SGLang
How to use AISE-TUDelft/CodeGPT-Multilingual 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 "AISE-TUDelft/CodeGPT-Multilingual" \ --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": "AISE-TUDelft/CodeGPT-Multilingual", "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 "AISE-TUDelft/CodeGPT-Multilingual" \ --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": "AISE-TUDelft/CodeGPT-Multilingual", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use AISE-TUDelft/CodeGPT-Multilingual with Docker Model Runner:
docker model run hf.co/AISE-TUDelft/CodeGPT-Multilingual
| {"errors": "replace", "unk_token": {"content": "<|UNKNOWN|>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "bos_token": {"content": "<s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "eos_token": {"content": "</s>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "pad_token": {"content": "<pad>", "single_word": false, "lstrip": false, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "add_prefix_space": false, "add_bos_token": false, "do_lower_case": false, "sep_token": "<EOL>", "additional_special_tokens": [], "model_max_length": 1024, "special_tokens_map_file": null, "name_or_path": "/scratch/tovandam/codegpt-codesearchnet/output/checkpoint-last", "tokenizer_class": "GPT2Tokenizer"} |