Spaces:
Paused
Paused
Update app.py
Browse files
app.py
CHANGED
@@ -2,7 +2,7 @@ import gradio as gr
|
|
2 |
import plotly.express as px
|
3 |
import os
|
4 |
import torch
|
5 |
-
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
|
6 |
|
7 |
# Check if CUDA is available and set device accordingly
|
8 |
device = "cuda" if torch.cuda.is_available() else "cpu"
|
@@ -25,14 +25,23 @@ def hermes_model():
|
|
25 |
|
26 |
|
27 |
def blender_model():
|
|
|
28 |
tokenizer = AutoTokenizer.from_pretrained("facebook/blenderbot-400M-distill")
|
29 |
-
model = AutoModelForCausalLM.from_pretrained("facebook/blenderbot-400M-distill", low_cpu_mem_usage=True, device_map="auto")
|
30 |
return model, tokenizer
|
31 |
|
32 |
model, tokenizer = blender_model()
|
33 |
|
34 |
-
# Function to generate a response from the model
|
35 |
def chat_response(msg_prompt: str) -> str:
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
36 |
"""
|
37 |
Generates a response from the model given a prompt.
|
38 |
|
|
|
2 |
import plotly.express as px
|
3 |
import os
|
4 |
import torch
|
5 |
+
from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline, BlenderbotForConditionalGeneration
|
6 |
|
7 |
# Check if CUDA is available and set device accordingly
|
8 |
device = "cuda" if torch.cuda.is_available() else "cpu"
|
|
|
25 |
|
26 |
|
27 |
def blender_model():
|
28 |
+
model = BlenderbotForConditionalGeneration.from_pretrained("facebook/blenderbot-400M-distill")
|
29 |
tokenizer = AutoTokenizer.from_pretrained("facebook/blenderbot-400M-distill")
|
|
|
30 |
return model, tokenizer
|
31 |
|
32 |
model, tokenizer = blender_model()
|
33 |
|
|
|
34 |
def chat_response(msg_prompt: str) -> str:
|
35 |
+
inputs = tokenizer([UTTERANCE], return_tensors="pt")
|
36 |
+
reply_ids = model.generate(**inputs)
|
37 |
+
outputs = tokenizer.batch_decode(reply_ids, skip_special_tokens=True)[0])
|
38 |
+
|
39 |
+
return outputs
|
40 |
+
except Exception as e:
|
41 |
+
return str(e)
|
42 |
+
|
43 |
+
# Function to generate a response from the model
|
44 |
+
def chat_responses(msg_prompt: str) -> str:
|
45 |
"""
|
46 |
Generates a response from the model given a prompt.
|
47 |
|