Text Generation
Transformers
Safetensors
code
t5
text2text-generation
codet5
code-repair
program-repair
bug-fixing
java
seq2seq
Eval Results (legacy)
text-generation-inference
Instructions to use thealper2/codet5-base-code-repair with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thealper2/codet5-base-code-repair with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="thealper2/codet5-base-code-repair")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("thealper2/codet5-base-code-repair") model = AutoModelForSeq2SeqLM.from_pretrained("thealper2/codet5-base-code-repair", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use thealper2/codet5-base-code-repair with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "thealper2/codet5-base-code-repair" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "thealper2/codet5-base-code-repair", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/thealper2/codet5-base-code-repair
- SGLang
How to use thealper2/codet5-base-code-repair 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 "thealper2/codet5-base-code-repair" \ --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": "thealper2/codet5-base-code-repair", "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 "thealper2/codet5-base-code-repair" \ --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": "thealper2/codet5-base-code-repair", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use thealper2/codet5-base-code-repair with Docker Model Runner:
docker model run hf.co/thealper2/codet5-base-code-repair
Download eval/qualitative_test.json from thealper2/codet5-base-code-repair: direct link, hf CLI and curl.
- Browser
- Download file 3 kB
-
https://huggingface.co/thealper2/codet5-base-code-repair/resolve/main/eval/qualitative_test.json
- Command line
-
hf download hf://thealper2/codet5-base-code-repair/eval/qualitative_test.json
-
curl -L -o qualitative_test.json https://huggingface.co/thealper2/codet5-base-code-repair/resolve/main/eval/qualitative_test.json
3 kB
| [ | |
| { | |
| "bucket": "exact", | |
| "index": "2", | |
| "buggy": "private void METHOD_1 ( java.lang.Class VAR_1 ) { android.content.Intent intent = new android.content.Intent ( this , VAR_1 ) ; METHOD_2 ( intent ) ; } \n", | |
| "reference": "public void METHOD_1 ( java.lang.Class VAR_1 ) { android.content.Intent intent = new android.content.Intent ( this , VAR_1 ) ; METHOD_2 ( intent ) ; }", | |
| "prediction": "public void METHOD_1 ( java.lang.Class VAR_1 ) { android.content.Intent intent = new android.content.Intent ( this , VAR_1 ) ; METHOD_2 ( intent ) ; }" | |
| }, | |
| { | |
| "bucket": "exact", | |
| "index": "6", | |
| "buggy": "private static boolean METHOD_1 ( final byte status ) { return status == ( VAR_1 ) ; } \n", | |
| "reference": "private static boolean METHOD_1 ( final int status ) { return status == ( VAR_1 ) ; }", | |
| "prediction": "private static boolean METHOD_1 ( final int status ) { return status == ( VAR_1 ) ; }" | |
| }, | |
| { | |
| "bucket": "partial", | |
| "index": "3", | |
| "buggy": "public void METHOD_1 ( ) { for ( TYPE_1 VAR_1 : VAR_2 ) VAR_1 . METHOD_2 ( ) ; METHOD_3 ( ) ; if ( ( VAR_3 ) != null ) VAR_3 . METHOD_1 ( ) ; } \n", | |
| "reference": "public void METHOD_1 ( ) { METHOD_3 ( ) ; if ( ( VAR_3 ) != null ) VAR_3 . METHOD_1 ( VAR_2 ) ; }", | |
| "prediction": "public void METHOD_1 ( ) { METHOD_3 ( ) ; if ( ( VAR_3 ) != null ) VAR_3 . METHOD_1 ( ) ; }" | |
| }, | |
| { | |
| "bucket": "partial", | |
| "index": "9", | |
| "buggy": "public void METHOD_1 ( final java.lang.String ... VAR_1 ) { if ( VAR_1 != null ) format . METHOD_2 ( ) . METHOD_3 ( VAR_2 , VAR_1 ) ; } \n", | |
| "reference": "public void METHOD_1 ( final java.lang.String ... VAR_1 ) { if ( ( VAR_1 != null ) && ( 0 < ( VAR_1 . length ) ) ) format . METHOD_2 ( ) . METHOD_3 ( VAR_2 , VAR_1 ) ; }", | |
| "prediction": "public void METHOD_1 ( final java.lang.String ... VAR_1 ) { if ( ( VAR_1 != null ) && ( ( format . METHOD_2 ( ) ) != null ) ) format . METHOD_2 ( ) . METHOD_3 ( VAR_2 , VAR_1 ) ; }" | |
| }, | |
| { | |
| "bucket": "incorrect", | |
| "index": "0", | |
| "buggy": "private TYPE_1 getType ( TYPE_2 VAR_1 ) { TYPE_3 VAR_2 = new TYPE_3 ( STRING_1 ) ; return new TYPE_1 ( VAR_2 , VAR_2 ) ; } \n", | |
| "reference": "private TYPE_1 getType ( TYPE_2 VAR_1 ) { TYPE_3 VAR_2 = new TYPE_3 ( STRING_1 ) ; return new TYPE_1 ( VAR_2 , VAR_2 , this , VAR_1 ) ; }", | |
| "prediction": "private TYPE_1 getType ( TYPE_2 VAR_1 ) { TYPE_3 VAR_2 = new TYPE_3 ( STRING_1 ) ; return new TYPE_1 ( VAR_2 , VAR_1 ) ; }" | |
| }, | |
| { | |
| "bucket": "incorrect", | |
| "index": "1", | |
| "buggy": "public TYPE_1 METHOD_1 ( ) { TYPE_1 output = VAR_1 [ VAR_2 ] ; if ( ( VAR_2 ) > 0 ) { VAR_2 = ( VAR_2 ) - 1 ; } else { } return output ; } \n", | |
| "reference": "public TYPE_1 METHOD_1 ( ) { TYPE_1 output = VAR_1 [ VAR_2 ] ; if ( ( VAR_2 ) >= 0 ) { VAR_2 = ( VAR_2 ) - 1 ; } else { } return output ; }", | |
| "prediction": "public TYPE_1 METHOD_1 ( ) { TYPE_1 output = VAR_1 [ VAR_2 ] ; if ( ( VAR_2 ) > 0 ) { VAR_2 = ( VAR_2 ) - 1 ; } return output ; }" | |
| } | |
| ] |