Instructions to use Salesforce/codet5-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Salesforce/codet5-large with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Salesforce/codet5-large")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelWithLMHead tokenizer = AutoTokenizer.from_pretrained("Salesforce/codet5-large") model = AutoModelWithLMHead.from_pretrained("Salesforce/codet5-large", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Salesforce/codet5-large with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Salesforce/codet5-large" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Salesforce/codet5-large", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Salesforce/codet5-large
- SGLang
How to use Salesforce/codet5-large 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 "Salesforce/codet5-large" \ --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": "Salesforce/codet5-large", "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 "Salesforce/codet5-large" \ --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": "Salesforce/codet5-large", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Salesforce/codet5-large with Docker Model Runner:
docker model run hf.co/Salesforce/codet5-large
Download model.safetensors from Salesforce/codet5-large: direct link, hf CLI and curl.
- Browser
- Download file 1.48 GB
-
https://huggingface.co/Salesforce/codet5-large/resolve/refs%2Fpr%2F3/model.safetensors
- Command line
-
hf download hf://Salesforce/codet5-large@refs/pr/3/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Salesforce/codet5-large/resolve/refs%2Fpr%2F3/model.safetensors
1.48 GB
- Xet hash:
- d0cf607f2ab7e590f5a2d9fbce81380727f708c7d84c4869b9f8f1f468e1b583
- Size of remote file:
- 1.48 GB
- SHA256:
- 81fa512a431d6eb375b17c4365b0c75e28f93d1f0df04a7f74ea12bad0d6d623
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