rakeshkiriyath
commited on
Commit
•
ffb8cc9
1
Parent(s):
2127d3e
Update README.md
Browse files
README.md
CHANGED
@@ -10,6 +10,7 @@ tags:
|
|
10 |
- sql
|
11 |
datasets:
|
12 |
- b-mc2/sql-create-context
|
|
|
13 |
---
|
14 |
# Model Card
|
15 |
|
@@ -18,23 +19,50 @@ datasets:
|
|
18 |
This is my first fine tuned LLM project.
|
19 |
|
20 |
|
21 |
-
##
|
22 |
|
23 |
-
|
|
|
24 |
|
25 |
-
|
|
|
26 |
|
27 |
-
|
|
|
28 |
|
29 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
30 |
|
31 |
|
32 |
#### Training Hyperparameters
|
33 |
|
34 |
-
num_train_epochs=1
|
35 |
-
per_device_train_batch_size=3
|
36 |
-
gradient_accumulation_steps=9
|
37 |
-
learning_rate=5e-5
|
38 |
weight_decay=0.01
|
39 |
|
40 |
|
|
|
10 |
- sql
|
11 |
datasets:
|
12 |
- b-mc2/sql-create-context
|
13 |
+
license: other
|
14 |
---
|
15 |
# Model Card
|
16 |
|
|
|
19 |
This is my first fine tuned LLM project.
|
20 |
|
21 |
|
22 |
+
## Usage
|
23 |
|
24 |
+
```
|
25 |
+
from transformers import GPT2LMHeadModel, GPT2Tokenizer
|
26 |
|
27 |
+
finetunedGPT = GPT2LMHeadModel.from_pretrained("rakeshkiriyath/gpt2Medium_text_to_sql")
|
28 |
+
finetunedTokenizer = GPT2Tokenizer.from_pretrained("rakeshkiriyath/gpt2Medium_text_to_sql")
|
29 |
|
30 |
+
def generate_text_to_sql(query, model, tokenizer, max_length=256):
|
31 |
+
prompt = f"Translate the following English question to SQL: {query}"
|
32 |
|
33 |
+
input_tensor = tokenizer.encode(prompt, return_tensors='pt').to('cuda')
|
34 |
+
|
35 |
+
output = model.generate(input_tensor, max_length=max_length, num_return_sequences=1, pad_token_id=tokenizer.eos_token_id)
|
36 |
+
|
37 |
+
decoded_output = tokenizer.decode(output[0], skip_special_tokens=True)
|
38 |
+
|
39 |
+
# Return only the SQL part (removing the input text)
|
40 |
+
sql_output = decoded_output[len(prompt):].strip()
|
41 |
+
|
42 |
+
return sql_output
|
43 |
+
|
44 |
+
queryList = ["I need a list of employees who joined in the company last 6 months with a salary hike of 30% ",
|
45 |
+
"Give me loginid,status,company of a user who is mapped to the organization XYZ "]
|
46 |
+
|
47 |
+
for query in queryList:
|
48 |
+
|
49 |
+
sql_result = generate_text_to_sql(query, finetunedGPT, finetunedTokenizer)
|
50 |
+
print(sql_result,"\n")
|
51 |
+
|
52 |
+
```
|
53 |
+
|
54 |
+
### Output
|
55 |
+
|
56 |
+
SELECT COUNT(*) FROM employees WHERE last_6_months = "6 months" AND salary_hike = "30%" \
|
57 |
+
SELECT loginid,status,company FROM user_mapped_to_organization WHERE mapping = "XYZ"
|
58 |
|
59 |
|
60 |
#### Training Hyperparameters
|
61 |
|
62 |
+
num_train_epochs=1 \
|
63 |
+
per_device_train_batch_size=3 \
|
64 |
+
gradient_accumulation_steps=9 \
|
65 |
+
learning_rate=5e-5 \
|
66 |
weight_decay=0.01
|
67 |
|
68 |
|