Spaces:
Sleeping
Sleeping
File size: 1,744 Bytes
21d3e5f e3ca7fc 21d3e5f c656b08 21d3e5f c656b08 21d3e5f c656b08 21d3e5f c656b08 21d3e5f c656b08 21d3e5f c656b08 e3ca7fc c656b08 21d3e5f | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 | # app.py
import gradio as gr
from transformers import AutoModelForCausalLM, AutoTokenizer
import torch
# -------------------------
# Model Setup
# -------------------------
model_name = "ibm-granite/granite-3.3-2b-instruct" # Smaller variant for Spaces
print("Loading tokenizer and model...")
tokenizer = AutoTokenizer.from_pretrained(model_name)
# Use device_map="auto" and 8-bit loading to reduce VRAM usage
model = AutoModelForCausalLM.from_pretrained(
model_name,
device_map="auto",
torch_dtype=torch.float16,
load_in_8bit=True, # If bitsandbytes installed
)
print(f"Model loaded on device: {model.device}")
# -------------------------
# Chat function
# -------------------------
def chat_with_granite(prompt):
try:
# Tokenize input and move tensors to the model device
inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
# Generate response
outputs = model.generate(
**inputs,
max_new_tokens=150,
do_sample=True,
temperature=0.7,
top_p=0.9
)
# Decode response
response = tokenizer.decode(outputs[0], skip_special_tokens=True)
return response
except Exception as e:
# Return error instead of crashing
return f"Error generating response: {e}"
# -------------------------
# Gradio Interface
# -------------------------
iface = gr.Interface(
fn=chat_with_granite,
inputs=gr.Textbox(lines=3, placeholder="Ask me something about finance..."),
outputs=gr.Textbox(),
title="Finance Chatbot",
description="Ask your finance questions and Granite will answer!",
allow_flagging="never"
)
# Launch interface
iface.launch()
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