Instructions to use lafarizo/code_translation_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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")

Notebooks
Google Colab
Kaggle
Local Apps

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
```

lafarizo commited on Nov 10, 2024

Commit

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Create README.md

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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)
+#### Evaluation
+- Failed