Upload 3 files
Browse files- app.py +63 -0
- gpt_model_quantized.pt +3 -0
- requirements.txt +1 -0
app.py
ADDED
@@ -0,0 +1,63 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import gradio as gr
|
2 |
+
import torch
|
3 |
+
import tiktoken
|
4 |
+
import numpy as np
|
5 |
+
from train import GPT, GPTConfig # Make sure to upload train.py to the Space
|
6 |
+
|
7 |
+
def load_quantized_model():
|
8 |
+
model = GPT(GPTConfig())
|
9 |
+
quantized_dict = torch.load("gpt_model_quantized.pt")
|
10 |
+
|
11 |
+
# Dequantize model
|
12 |
+
state_dict = {}
|
13 |
+
for key, value in quantized_dict.items():
|
14 |
+
if isinstance(value, dict):
|
15 |
+
state_dict[key] = torch.tensor(
|
16 |
+
value['data'].astype(np.float32) * value['scale']
|
17 |
+
)
|
18 |
+
else:
|
19 |
+
state_dict[key] = value
|
20 |
+
|
21 |
+
model.load_state_dict(state_dict)
|
22 |
+
model.eval()
|
23 |
+
return model
|
24 |
+
|
25 |
+
def generate_text(input_text):
|
26 |
+
try:
|
27 |
+
# Set device
|
28 |
+
device = 'cuda' if torch.cuda.is_available() else 'cpu'
|
29 |
+
|
30 |
+
# Load model
|
31 |
+
model = load_quantized_model()
|
32 |
+
model = model.to(device)
|
33 |
+
|
34 |
+
# Tokenize input
|
35 |
+
tokenizer = tiktoken.get_encoding('gpt2')
|
36 |
+
input_tokens = torch.tensor([tokenizer.encode(input_text)]).to(device)
|
37 |
+
|
38 |
+
# Generate
|
39 |
+
with torch.no_grad():
|
40 |
+
output_tokens = model.generate(input_tokens, max_new_tokens=500)[0].tolist()
|
41 |
+
|
42 |
+
# Decode and return
|
43 |
+
generated_text = tokenizer.decode(output_tokens)
|
44 |
+
return generated_text
|
45 |
+
except Exception as e:
|
46 |
+
return f"Error generating text: {e}"
|
47 |
+
|
48 |
+
# Create Gradio interface
|
49 |
+
iface = gr.Interface(
|
50 |
+
fn=generate_text,
|
51 |
+
inputs=gr.Textbox(lines=5, label="Input Text"),
|
52 |
+
outputs=gr.Textbox(lines=10, label="Generated Text"),
|
53 |
+
title="GPT Text Generator",
|
54 |
+
description="Enter some text and the model will generate a continuation.",
|
55 |
+
examples=[
|
56 |
+
["The quick brown fox"],
|
57 |
+
["In a world where AI"],
|
58 |
+
["Once upon a time"]
|
59 |
+
]
|
60 |
+
)
|
61 |
+
|
62 |
+
# Launch the interface
|
63 |
+
iface.launch()
|
gpt_model_quantized.pt
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:84ddd50901ce047532e6587705beb5768740afc9879c4652094b842dd913c41c
|
3 |
+
size 255934032
|
requirements.txt
ADDED
@@ -0,0 +1 @@
|
|
|
|
|
1 |
+
|