Update README.md

README.md

@@ -424,7 +424,7 @@ Domain and content type classification probabilities:
 
 ## How to Load the Dataset
 
-This section provides examples of how to load the `EssentialAI/eai-taxonomy-code-w-dclm` dataset using different Python libraries and frameworks.
+This section provides examples of how to load the `EssentialAI/eai-taxonomy-code-w-dclm-100b-sample` dataset using different Python libraries and frameworks.
 
 ### Using Hugging Face Datasets (Standard Method)
 
@@ -434,7 +434,7 @@ The simplest way to load the dataset is using the Hugging Face `datasets` librar
 from datasets import load_dataset
 
 # Load the entire dataset
-dataset = load_dataset("EssentialAI/eai-taxonomy-code-w-dclm")
+dataset = load_dataset("EssentialAI/eai-taxonomy-code-w-dclm-100b-sample")
 
 # View dataset structure
 print(dataset)
@@ -447,7 +447,7 @@ You can also load the dataset in streaming mode to avoid downloading the entire
 from datasets import load_dataset
 
 # Load in streaming mode
-dataset = load_dataset("EssentialAI/eai-taxonomy-code-w-dclm", streaming=True)
+dataset = load_dataset("EssentialAI/eai-taxonomy-code-w-dclm-100b-sample", streaming=True)
 data_stream = dataset["train"]
 
 # Iterate through examples
@@ -470,7 +470,7 @@ from pyspark.sql import SparkSession
 spark = SparkSession.builder.appName("EAI-Taxonomy-Code-w-DCLM").getOrCreate()
 
 # Load the dataset using the "huggingface" data source
-df = spark.read.format("huggingface").load("EssentialAI/eai-taxonomy-code-w-dclm")
+df = spark.read.format("huggingface").load("EssentialAI/eai-taxonomy-code-w-dclm-100b-sample")
 
 # Basic dataset exploration
 print(f"Dataset shape: {df.count()} rows, {len(df.columns)} columns")
@@ -481,7 +481,7 @@ df.printSchema()
 df_subset = (
     spark.read.format("huggingface")
     .option("columns", '["column1", "column2"]')  # Replace with actual column names
-    .load("EssentialAI/eai-taxonomy-code-w-dclm")
+    .load("EssentialAI/eai-taxonomy-code-w-dclm-100b-sample")
 )
 
 # Run SQL queries on the dataset
@@ -501,7 +501,7 @@ Daft provides a modern DataFrame library optimized for machine learning workload
 import daft
 
 # Load the entire dataset
-df = daft.read_parquet("hf://datasets/EssentialAI/eai-taxonomy-code-w-dclm")
+df = daft.read_parquet("hf://datasets/EssentialAI/eai-taxonomy-code-w-dclm-100b-sample")
 
 # Basic exploration
 print("Dataset schema:")
@@ -518,7 +518,7 @@ import daft
 from daft.io import IOConfig, HTTPConfig
 
 io_config = IOConfig(http=HTTPConfig(bearer_token="your_token"))
-df = daft.read_parquet("hf://datasets/EssentialAI/eai-taxonomy-code-w-dclm", io_config=io_config)
+df = daft.read_parquet("hf://datasets/EssentialAI/eai-taxonomy-code-w-dclm-100b-sample", io_config=io_config)
 ```
 
 ### Installation Requirements