Update app.py
Browse files
app.py
CHANGED
|
@@ -4,11 +4,22 @@ import gradio as grad
|
|
| 4 |
mdl = GPT2LMHeadModel.from_pretrained('gpt2')
|
| 5 |
gpt2_tkn=GPT2Tokenizer.from_pretrained('gpt2')
|
| 6 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 7 |
def generate(starting_text):
|
| 8 |
tkn_ids = gpt2_tkn.encode(starting_text, return_tensors = 'pt')
|
| 9 |
gpt2_tensors = mdl.generate(tkn_ids)
|
| 10 |
-
response
|
|
|
|
|
|
|
|
|
|
|
|
|
| 11 |
return response
|
|
|
|
| 12 |
txt=grad.Textbox(lines=1, label="English", placeholder="English Text here")
|
| 13 |
out=grad.Textbox(lines=1, label="Generated Tensors")
|
| 14 |
grad.Interface(generate, inputs=txt, outputs=out).launch()
|
|
|
|
| 4 |
mdl = GPT2LMHeadModel.from_pretrained('gpt2')
|
| 5 |
gpt2_tkn=GPT2Tokenizer.from_pretrained('gpt2')
|
| 6 |
|
| 7 |
+
# def generate(starting_text):
|
| 8 |
+
# tkn_ids = gpt2_tkn.encode(starting_text, return_tensors = 'pt')
|
| 9 |
+
# gpt2_tensors = mdl.generate(tkn_ids)
|
| 10 |
+
# response = gpt2_tensors
|
| 11 |
+
# return response
|
| 12 |
+
|
| 13 |
def generate(starting_text):
|
| 14 |
tkn_ids = gpt2_tkn.encode(starting_text, return_tensors = 'pt')
|
| 15 |
gpt2_tensors = mdl.generate(tkn_ids)
|
| 16 |
+
response=""
|
| 17 |
+
#response = gpt2_tensors
|
| 18 |
+
for i, x in enumerate(gpt2_tensors):
|
| 19 |
+
response=response+f"{i}: {gpt2_tkn.decode(x, skip_
|
| 20 |
+
special_tokens=True)}"
|
| 21 |
return response
|
| 22 |
+
|
| 23 |
txt=grad.Textbox(lines=1, label="English", placeholder="English Text here")
|
| 24 |
out=grad.Textbox(lines=1, label="Generated Tensors")
|
| 25 |
grad.Interface(generate, inputs=txt, outputs=out).launch()
|