
LLM: [Salesforce/CodeGen-6B-Mono](https://huggingface.co/Salesforce/codegen-6B-mono)

I'm using [Peft](https://github.com/huggingface/peft) for tuning

Tuning: 
- [LoRA](https://github.com/microsoft/LoRA)
- [Leetcode](https://huggingface.co/datasets/mhhmm/leetcode-solutions-python)
- [Google Deepmind Code contests](https://huggingface.co/datasets/deepmind/code_contests)
- Google Colab Pro+ in ~2 hours, shoutout to my friend TieuPhuong
{"language": ["en"], "license": "mit", "library_name": "transformers", "datasets": ["mhhmm/leetcode-solutions-python", "deepmind/code_contests"], "pipeline_tag": "text-generation", "widget": [{"text": " # Given an array of integers, return indices of the two numbers such that they add up to a specific target\n\ndef twoSum(array, target) -> List[int]: ", "example_title": "Twosum problem"}]}
transformers codegen text-generation en dataset:mhhmm/leetcode-solutions-python dataset:deepmind/code_contests license:mit autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #codegen #text-generation #en #dataset-mhhmm/leetcode-solutions-python #dataset-deepmind/code_contests #license-mit #autotrain_compatible #endpoints_compatible #region-us 


LLM: Salesforce/CodeGen-6B-Mono

I'm using Peft for tuning

Tuning: 
- LoRA
- Leetcode
- Google Deepmind Code contests
- Google Colab Pro+ in ~2 hours, shoutout to my friend TieuPhuong
TAGS
#transformers #codegen #text-generation #en #dataset-mhhmm/leetcode-solutions-python #dataset-deepmind/code_contests #license-mit #autotrain_compatible #endpoints_compatible #region-us 

TAGS
#transformers #codegen #text-generation #en #dataset-mhhmm/leetcode-solutions-python #dataset-deepmind/code_contests #license-mit #autotrain_compatible #endpoints_compatible #region-us 
