Update README.md

README.md

@@ -12,6 +12,37 @@ pipeline_tag: text-generation
 TituLM-1B-BN-V1 is a large language model specifically trained for generating and understanding Bangla text. Utilizing a decoder-style transformer architecture, this model has been extensively trained on a dataset comprising 4.51 billion Bangla tokens. This model is the part of iterative train and release Bangla LLM from Hishab.
 
 ## Training
-The training process was managed using the robust framework provided by MosaicML's [llm-foundry](https://github.com/mosaicml/llm-foundry) repository. Throughout the training phase, titulm-1b-bn-v1 underwent a total of 59 iterations, allowing for iterative refinements and optimization
+The training process was managed using the robust framework provided by MosaicML's [llm-foundry](https://github.com/mosaicml/llm-foundry) repository. Throughout the training phase, titulm-1b-bn-v1 underwent a total of 59 iterations, allowing for iterative refinements and optimization.
+Notable training configs:
+
+- n_nead: 16
+- n_layers: 24
+- max_sequence_length: 2048
+- vocab_size: 72000
+- attn_impl: flash
 
 ## Datasets
+We add Bangla text datasets from several sources including
+
+- Culturax
+- Books
+- Bangla Wikipedia
+- Banglapedia
+- News articles
+
+Our total data size is 58 GB of deduplicated data with 4.51 billion tokens tokenized by our sentencepiece model.
+
+
+## How to Use
+The basic use cases to generate text using this model is simple. Follow the below code to generate text using this model.
+
+Install the following library before running the code:
+
+- pip install transofrmers
+- pip install einops
+- pip install accelerate
+
+```py
+# code will add soon
+```
+