File size: 3,199 Bytes
a995440 |
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 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 |
import torch
from transformers import pipeline, logging, AutoModelForCausalLM, AutoTokenizer
import gradio as gr
## 1 - Loading Model
## 1 - Loading Model
model = AutoModelForCausalLM.from_pretrained(
"microsoft/phi-2",
torch_dtype=torch.float32,
device_map="auto",
trust_remote_code=True
)
model.load_adapter('checkpoint-960')
## 2 - Loading Tokenizer
tokenizer = AutoTokenizer.from_pretrained('checkpoint-960', trust_remote_code=True)
tokenizer.pad_token = tokenizer.eos_token
def generate_dialogue(input_text):
pipe = pipeline(task="text-generation",model=model,tokenizer=tokenizer,max_length=100)
result = pipe(f"<s>[INST] {input_text} [/INST]")
return result[0]['generated_text']
HTML_TEMPLATE = """
<style>
#app-header {
text-align: center;
background: rgba(255, 255, 255, 0.3); /* Semi-transparent white */
padding: 20px;
border-radius: 10px;
box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
position: relative; /* To position the artifacts */
}
#app-header h1 {
color: #FF0000;
font-size: 2em;
margin-bottom: 10px;
}
.concept {
position: relative;
transition: transform 0.3s;
}
.concept:hover {
transform: scale(1.1);
}
.concept img {
width: 100px;
border-radius: 10px;
box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
}
.concept-description {
position: absolute;
bottom: -30px;
left: 50%;
transform: translateX(-50%);
background-color: #4CAF50;
color: white;
padding: 5px 10px;
border-radius: 5px;
opacity: 0;
transition: opacity 0.3s;
}
.concept:hover .concept-description {
opacity: 1;
}
/* Artifacts */
</style>
<div id="app-header">
<!-- Artifacts -->
<div class="artifact large"></div>
<div class="artifact large"></div>
<div class="artifact large"></div>
<div class="artifact large"></div>
<!-- Content -->
<h1>CHAT with fine tuned Phi-2 LLM</h1>
<p>Generate dialogue for given some initial prompt for context.</p>
<p>Model: Phi-2 (https://huggingface.co/microsoft/phi-2), Dataset: oasst1 (https://huggingface.co/datasets/OpenAssistant/oasst1) </p>
"""
with gr.Blocks(theme=gr.themes.Glass(),css=".gradio-container {background: url('https://github.com/Manjunath-Yelipeta/S27_Era/blob/main/bg.jpg?raw=true')}") as interface:
gr.HTML(value=HTML_TEMPLATE, show_label=False)
gr.Markdown("")
gr.Markdown("")
gr.Markdown("")
gr.Markdown("")
gr.Markdown("")
gr.Markdown("")
gr.Markdown("")
gr.Markdown("")
gr.Markdown("")
gr.Markdown("")
gr.Markdown("")
with gr.Row():
input_text = gr.Textbox(
label="Input Text",
value="Enter your prompt here: This text will set the context for the AI's response."
)
outputs = gr.Textbox(
label="Answer"
)
inputs = [input_text]
with gr.Column():
button = gr.Button("Ask me")
button.click(generate_dialogue, inputs=inputs, outputs=outputs)
interface.launch()
|