code-analysis
Qwen3.8-27B-abliterated-code-analysis-preview-mtp-GGUFQwen3.8-27B-abliterated-code-analysis-previewturkish-sentiment-analysiscodeswitch-spaeng-sentiment-analysis-linceturkish-sentiment-analysis-finetunedcodellama-pattern-analysisgemma-Code-Instruct-Finetune-Bank-Analysis-By-ManishQwen3-Coder-30B-A3B-HF_sft_mle_execution_tree_and_analysis
routing_analysis-code-data
routing_analysis — code and data
This dataset repository stores the non-checkpoint portion of the
routing_analysis filesystem snapshot as individual files under their
original relative paths. Files are uploaded directly; they are not packed into
split tar archives.
The selection is enumerated from the filesystem and does not consult
.gitignore. Ignored files and .gitignore files themselves are therefore
included whenever they belong to the code/data selection.
Training… See the full description on the dataset page: https://huggingface.co/datasets/lylybig/routing_analysis-code-data.code-analysis-sft-qwen38-v2Code-Mixed-Sentiment-Analysis-Dataset
Dataset Generation:
Initially, we select the Amazon Review Dataset as our base data, referenced from Ni et al. (2019)[^1]. We randomly extract 100,000 instances from this dataset. The original labels in this dataset are ratings, scaled from 1 to 5. For our specific task, we categorize them into Positive (rating > 3), Neutral (rating = 3), and Negative (rating < 3), ensuring a balanced number of instances for each label. To generate the synthetic Code-mixed dataset, we apply two… See the full description on the dataset page: https://huggingface.co/datasets/md-nishat-008/Code-Mixed-Sentiment-Analysis-Dataset.instruct_code_for_data_analysiscode_completion_for_data_analysismmlu-olmo37b-stage2-math-code-analysis-with-context