Text Generation
Transformers
Safetensors
gpt_bigcode
code-translation
code-to-code
java
csharp
text-generation-inference
Instructions to use lafarizo/code_translation_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lafarizo/code_translation_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="lafarizo/code_translation_v2")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("lafarizo/code_translation_v2") model = AutoModelForCausalLM.from_pretrained("lafarizo/code_translation_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use lafarizo/code_translation_v2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "lafarizo/code_translation_v2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "lafarizo/code_translation_v2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/lafarizo/code_translation_v2
- SGLang
How to use lafarizo/code_translation_v2 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 "lafarizo/code_translation_v2" \ --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": "lafarizo/code_translation_v2", "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 "lafarizo/code_translation_v2" \ --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": "lafarizo/code_translation_v2", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use lafarizo/code_translation_v2 with Docker Model Runner:
docker model run hf.co/lafarizo/code_translation_v2
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title: "Code Translation v2"
tags:
- code-translation
- code-to-code
- java
- csharp
library_name: "transformers"
datasets:
- google/code_x_glue_cc_code_to_code_trans
widget:
- text: "public class HelloWorld { public static void main(String[] args) { System.out.println(\"Hello, World!\"); } }"
---
# Code Translation v2
Code Translation from Java to C#
### Model Sources
- **Repository:** [bigcode/tiny_starcoder_py](https://huggingface.co/bigcode/tiny_starcoder_py)
### Dataset
- **Repository:** [google/code_x_glue_cc_code_to_code_trans](https://huggingface.co/datasets/google/code_x_glue_cc_code_to_code_trans)
### Testing Data
- [Testing Data](https://huggingface.co/datasets/google/code_x_glue_cc_code_to_code_trans/viewer/default/test)
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