Upload README.md with huggingface_hub

README.md

@@ -0,0 +1,56 @@
+# Resume Dataset
+
+## Dataset Description
+
+This dataset contains resume data for different job categories with skills, education, and experience information that can be used for resume classification or career prediction applications.
+
+### Data Structure
+
+This dataset is stored in CSV format with the following columns:
+- `id`: Unique identifier for each resume
+- `category`: Job category or field (e.g., HR, IT, Marketing)
+- `skills`: Comma-separated list of skills mentioned in the resume
+- `education`: Comma-separated list of education qualifications
+- `experience`: Comma-separated list of job experiences
+
+### Dataset Splits
+
+- `train`: Main training dataset
+- `eval`: Evaluation dataset (last 200 samples)
+
+## Usage
+
+You can load this dataset using the Hugging Face datasets library:
+
+```python
+from datasets import load_dataset
+
+# Load the entire dataset
+dataset = load_dataset("C0ldSmi1e/resume-dataset")
+
+# Access specific splits
+train_data = dataset["train"]
+eval_data = dataset["eval"]
+
+# Check the columns
+print(train_data.column_names)
+
+# Access a sample entry
+print(train_data[0])
+```
+
+## Example: Using with a Tokenizer
+
+```python
+from datasets import load_dataset
+from transformers import AutoTokenizer
+
+# Load a tokenizer
+tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")
+EOS_TOKEN = tokenizer.eos_token  # End of sequence token
+
+# Load your dataset
+dataset = load_dataset("C0ldSmi1e/resume-dataset")
+train_data = dataset["train"]
+eval_data = dataset["eval"]
+```