Update README.md

README.md

@@ -1,21 +1,58 @@
----
-dataset_info:
-  features:
-  - name: doc_id
-    dtype: string
-  - name: type
-    dtype: string
-  - name: text
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 25324509618
-    num_examples: 806930
-  download_size: 9419131940
-  dataset_size: 25324509618
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
----
+---
+dataset_info:
+  features:
+  - name: doc_id
+    dtype: string
+  - name: type
+    dtype: string
+  - name: text
+    dtype: string
+  splits:
+  - name: train
+    num_bytes: 25324509618
+    num_examples: 806930
+  download_size: 9419131940
+  dataset_size: 25324509618
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+license: cc-by-4.0
+task_categories:
+- text-generation
+language:
+- hi
+- en
+pretty_name: 'long-context '
+size_categories:
+- 100K<n<1M
+---
+
+# Dataset 
+
+This dataset was filtered from AI4BHarat dataset [sangraha](https://huggingface.co/datasets/ai4bharat/sangraha),which is the largest high-quality, cleaned Indic language pretraining data containing 251B tokens summed up over 22 languages, extracted from curated sources, existing multilingual corpora and large scale translations.
+
+This dataset only  Hindi as of now 
+
+# Information 
+* First this dataset is mainly for long context training 
+* The minimum len is  and maximum len is
+
+# Getting started 
+
+For downloading the entire dataset:
+```
+from datasets import load_dataset
+
+dataset = load_dataset("damerajee/long_context_hindi")
+```
+If dataset is too big you can simply stream:
+```
+from datasets import load_dataset
+
+dataset = load_dataset("damerajee/long_context_hindi",split='train',streaming=True)
+```
+```
+dataset.take(2)
+```