Update README.md

README.md

@@ -1,14 +1,36 @@
 ---
-# For reference on model card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/modelcard.md?plain=1
-# Doc / guide: https://huggingface.co/docs/hub/model-cards
-
 widget:
-- text: "sql_prompt: What is the monthly voice usage for each customer in the Mumbai region? sql_context: CREATE TABLE customers (customer_id INT, name VARCHAR(50), voice_usage_minutes FLOAT, region VARCHAR(50)); INSERT INTO customers (customer_id, name, voice_usage_minutes, region) VALUES (1, 'Aarav Patel', 500, 'Mumbai'), (2, 'Priya Shah', 700, 'Mumbai');"
-  example_title: "Example1"
-- text: "sql_prompt: How many wheelchair accessible vehicles are there in the 'Train' mode of transport? sql_context: CREATE TABLE Vehicles(vehicle_id INT, vehicle_type VARCHAR(20), mode_of_transport VARCHAR(20), is_wheelchair_accessible BOOLEAN); INSERT INTO Vehicles(vehicle_id, vehicle_type, mode_of_transport, is_wheelchair_accessible) VALUES (1, 'Train_Car', 'Train', TRUE), (2, 'Train_Engine', 'Train', FALSE), (3, 'Bus', 'Bus', TRUE);"
-  example_title: "Example2"
-- text: "sql_prompt: Which economic diversification efforts in the 'diversification' table have a higher budget than the average budget for all economic diversification efforts in the 'budget' table? sql_context: CREATE TABLE diversification (id INT, effort VARCHAR(50), budget FLOAT); CREATE TABLE budget (diversification_id INT, diversification_effort VARCHAR(50), amount FLOAT);"
-  example_title: "Example3"
+- text: >-
+    sql_prompt: What is the monthly voice usage for each customer in the Mumbai
+    region? sql_context: CREATE TABLE customers (customer_id INT, name
+    VARCHAR(50), voice_usage_minutes FLOAT, region VARCHAR(50)); INSERT INTO
+    customers (customer_id, name, voice_usage_minutes, region) VALUES (1, 'Aarav
+    Patel', 500, 'Mumbai'), (2, 'Priya Shah', 700, 'Mumbai');
+  example_title: Example1
+- text: >-
+    sql_prompt: How many wheelchair accessible vehicles are there in the 'Train'
+    mode of transport? sql_context: CREATE TABLE Vehicles(vehicle_id INT,
+    vehicle_type VARCHAR(20), mode_of_transport VARCHAR(20),
+    is_wheelchair_accessible BOOLEAN); INSERT INTO Vehicles(vehicle_id,
+    vehicle_type, mode_of_transport, is_wheelchair_accessible) VALUES (1,
+    'Train_Car', 'Train', TRUE), (2, 'Train_Engine', 'Train', FALSE), (3, 'Bus',
+    'Bus', TRUE);
+  example_title: Example2
+- text: >-
+    sql_prompt: Which economic diversification efforts in the 'diversification'
+    table have a higher budget than the average budget for all economic
+    diversification efforts in the 'budget' table? sql_context: CREATE TABLE
+    diversification (id INT, effort VARCHAR(50), budget FLOAT); CREATE TABLE
+    budget (diversification_id INT, diversification_effort VARCHAR(50), amount
+    FLOAT);
+  example_title: Example3
+language:
+- en
+datasets:
+- gretelai/synthetic_text_to_sql
+metrics:
+- rouge
+library_name: transformers
 ---
 
 
@@ -37,18 +59,22 @@ Addressing the power of LLM in fintuned downstream task. Implemented as a person
 ### How to use
 
 # Load model directly
+```python
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
 tokenizer = AutoTokenizer.from_pretrained("SwastikM/bart-large-nl2sql")
 
 model = AutoModelForSeq2SeqLM.from_pretrained("SwastikM/bart-large-nl2sql")
 
-query_question_with_context = "sql_prompt: Which economic diversification efforts in the 'diversification' table have a higher budget than the average budget for all economic diversification efforts in the 'budget' table? sql_context: CREATE TABLE diversification (id INT, effort VARCHAR(50), budget FLOAT); CREATE TABLE budget (diversification_id INT, diversification_effort VARCHAR(50), amount FLOAT);"
+query_question_with_context = """sql_prompt: Which economic diversification efforts in
+the 'diversification' table have a higher budget than the average budget for all economic diversification efforts in the 'budget' table?
+sql_context: CREATE TABLE diversification (id INT, effort VARCHAR(50), budget FLOAT); CREATE TABLE
+budget (diversification_id INT, diversification_effort VARCHAR(50), amount FLOAT);"""
 
 sql = model.generate(text)
 
 print(sql)
-
+```
 
 
 ## Training Details
@@ -57,8 +83,6 @@ print(sql)
 
 [gretelai/synthetic_text_to_sql](https://huggingface.co/datasets/gretelai/synthetic_text_to_sql)
 
-[More Information Needed]
-
 ### Training Procedure
 
 HuggingFace Accelerate with Training Loop.
@@ -89,7 +113,7 @@ HuggingFace Accelerate with Training Loop.
 
 #### Hardware
 
--**GPU:** P100
+- **GPU:** P100
 
 
 ## Citation
@@ -132,4 +156,4 @@ HuggingFace Accelerate with Training Loop.
 
 ## Model Card Authors
 
-Swastik Maiti
+Swastik Maiti