Update README.md

README.md

@@ -5,6 +5,7 @@ datasets:
 - m-a-p/Code-Feedback
 - openbmb/UltraInteract_sft
 - ise-uiuc/Magicoder-Evol-Instruct-110K
+- flytech/python-codes-25k
 language:
 - en
 metrics:
@@ -16,11 +17,8 @@ tags:
 ## AIGCodeGeek-DS-6.7B
 
 ### Introduction
-AIGCodeGeek-DS-6.7B is the first version of our Code-LLM family with competitive performance on benchmarks such as HumanEval(+) and MBPP(+).
-
-It gains a lot of insights from the open-source community and we deeply appreciate all of these great works.
-
-We are preparing for the tech report, so stay tuned for more details:)
+AIGCodeGeek-DS-6.7B is the first released version of our Code-LLM family with competitive performance on benchmarks such as HumanEval(+) and MBPP(+).
+We are preparing for a tech report; stay tuned for more details:)
 
 ### Model Details
 #### Model Description
@@ -29,11 +27,10 @@ We are preparing for the tech report, so stay tuned for more details:)
 - Fine-tuned from [deepseek-ai/deepseek-coder-6.7b-base](https://huggingface.co/deepseek-ai/deepseek-coder-6.7b-base) with full parameters
 
 ### Training data
-A mixture of both
-- samples from several high-quality open-source datasets (read *Acknowledgements*),
-- our private datasets (already decontaminated with benchmarks).
+A mixture of samples from high-quality open-source datasets (read *Acknowledgements*).
 
 ### Evaluation
+
 To check out our evaluation results: [EvalPlus](https://evalplus.github.io/leaderboard.html)
 
 ### Requirements
@@ -59,8 +56,10 @@ TBD
 
 
 ### Acknowledgements
-- [WizardCoder](https://github.com/nlpxucan/WizardLM/tree/main/WizardCoder): WizardLM-Evol-Instruct V2 datasets
-  - We used a back-up([Leon-Leee/wizardlm_evol_instruct_v2_196K_backuped](https://huggingface.co/datasets/Leon-Leee/wizardlm_evol_instruct_v2_196K_backuped)) since this dataset has been deleted.
-- [Magicoder](https://github.com/ise-uiuc/magicoder/): [Magicoder-Evol-Instruct-110K](https://huggingface.co/datasets/ise-uiuc/Magicoder-Evol-Instruct-110K) from theblackcat102/evol-codealpaca-v1(https://huggingface.co/datasets/theblackcat102/evol-codealpaca-v1)
-- [Eurus](https://github.com/OpenBMB/Eurus): reasoning enhancement dataset of [openbmb/UltraInteract_sft](https://huggingface.co/datasets/openbmb/UltraInteract_sft)
-- [OpenCoderInterpreter](https://opencodeinterpreter.github.io/): [m-a-p/Code-Feedback](https://huggingface.co/datasets/m-a-p/Code-Feedback)
+We gain a lot of knowledge and resources from the open-source community:
+- [DeepSeekCoder](https://huggingface.co/deepseek-ai): impressive performance and insightful tech reports
+- [WizardCoder](https://github.com/nlpxucan/WizardLM/tree/main/WizardCoder): Evol Instruct method and datasets
+  - We used a ([Leon-Leee/wizardlm_evol_instruct_v2_196K_backuped](https://huggingface.co/datasets/Leon-Leee/wizardlm_evol_instruct_v2_196K_backuped)) since this original has been deleted.
+- [Magicoder](https://github.com/ise-uiuc/magicoder/): OSS-Instruct method and datasets, [Magicoder-Evol-Instruct-110K](https://huggingface.co/datasets/ise-uiuc/Magicoder-Evol-Instruct-110K) from theblackcat102/evol-codealpaca-v1(https://huggingface.co/datasets/theblackcat102/evol-codealpaca-v1)
+- [Eurus](https://github.com/OpenBMB/Eurus): creative methods and datasets for reasoning, [openbmb/UltraInteract_sft](https://huggingface.co/datasets/openbmb/UltraInteract_sft)
+- [OpenCoderInterpreter](https://opencodeinterpreter.github.io/): well-designed experiments and [m-a-p/Code-Feedback](https://huggingface.co/datasets/m-a-p/Code-Feedback)