Spaces:
Sleeping
Sleeping
Update app.py
Browse files
app.py
CHANGED
@@ -5,10 +5,6 @@ from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
|
|
5 |
"""
|
6 |
For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
|
7 |
"""
|
8 |
-
#client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
|
9 |
-
#client = InferenceClient("vennify/t5-base-grammar-correction")
|
10 |
-
#gr.load("models/vennify/t5-base-grammar-correction").launch()
|
11 |
-
|
12 |
# Load the model and tokenizer
|
13 |
model_name = "vennify/t5-base-grammar-correction"
|
14 |
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
|
@@ -28,15 +24,7 @@ def correct_text(text, max_length, num_beams, temperature, top_p):
|
|
28 |
return corrected_text
|
29 |
|
30 |
|
31 |
-
def respond(
|
32 |
-
message,
|
33 |
-
history: list[tuple[str, str]],
|
34 |
-
system_message,
|
35 |
-
max_tokens,
|
36 |
-
num_beams,
|
37 |
-
temperature,
|
38 |
-
top_p,
|
39 |
-
):
|
40 |
#messages = [{"role": "system", "content": system_message}]
|
41 |
|
42 |
#for val in history:
|
@@ -47,7 +35,7 @@ def respond(
|
|
47 |
|
48 |
#messages.append({"role": "user", "content": message})
|
49 |
|
50 |
-
response = correct_text(message,
|
51 |
yield response
|
52 |
|
53 |
"""
|
@@ -57,7 +45,8 @@ demo = gr.ChatInterface(
|
|
57 |
respond,
|
58 |
additional_inputs=[
|
59 |
gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
|
60 |
-
gr.Slider(minimum=1, maximum=2048, value=
|
|
|
61 |
gr.Slider(minimum=1, maximum=10, value=5, step=1, label="Num Beams"),
|
62 |
gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
|
63 |
gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
|
|
|
5 |
"""
|
6 |
For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
|
7 |
"""
|
|
|
|
|
|
|
|
|
8 |
# Load the model and tokenizer
|
9 |
model_name = "vennify/t5-base-grammar-correction"
|
10 |
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
|
|
|
24 |
return corrected_text
|
25 |
|
26 |
|
27 |
+
def respond(message, history: list[tuple[str, str]], system_message, max_length, min_length, num_beams, temperature, top_p):
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
28 |
#messages = [{"role": "system", "content": system_message}]
|
29 |
|
30 |
#for val in history:
|
|
|
35 |
|
36 |
#messages.append({"role": "user", "content": message})
|
37 |
|
38 |
+
response = correct_text(message, max_length, min_length, num_beams, temperature, top_p)
|
39 |
yield response
|
40 |
|
41 |
"""
|
|
|
45 |
respond,
|
46 |
additional_inputs=[
|
47 |
gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
|
48 |
+
gr.Slider(minimum=1, maximum=2048, value=100, step=1, label="Max Length"),
|
49 |
+
gr.Slider(minimum=1, maximum=2048, value=0, step=1, label="Min Length"),
|
50 |
gr.Slider(minimum=1, maximum=10, value=5, step=1, label="Num Beams"),
|
51 |
gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
|
52 |
gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
|