File size: 3,924 Bytes
17d3814
 
 
fa55388
f4b9dcc
17d3814
 
ad35440
 
17d3814
 
 
ad35440
17d3814
 
 
 
 
f4b9dcc
 
5a2e45f
 
574defd
2f65e28
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ad35440
17d3814
 
 
 
cd08250
17d3814
 
9bb21cf
f4b9dcc
cbecf21
17d3814
 
 
ad35440
17d3814
 
 
f4b9dcc
 
 
 
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
import spaces
import gradio as gr
import torch
import transformers
from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig
import os

title = """# Welcome to 🌟Tonic's✨StarCoder
✨StarCoder StarCoder2-15B model is a 15B parameter model trained on 600+ programming languages from The Stack v2, with opt-out requests excluded. The model uses Grouped Query Attention, a context window of 16,384 tokens with a sliding window attention of 4,096 tokens, and was trained using the Fill-in-the-Middle objective on 4+ trillion tokens. The model was trained with NVIDIA NeMo™ Framework using the NVIDIA Eos Supercomputer built with NVIDIA DGX H100 systems. You can build with this endpoint using✨StarCoder available here : [bigcode/starcoder2-15b](https://huggingface.co./bigcode/starcoder2-15b). You can also use ✨StarCoder by cloning this space. Simply click here: <a style="display:inline-block" href="https://huggingface.co./spaces/Tonic/starcoder2?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a></h3> 
Join us : 🌟TeamTonic🌟 is always making cool demos! Join our active builder's 🛠️community 👻 [![Join us on Discord](https://img.shields.io/discord/1109943800132010065?label=Discord&logo=discord&style=flat-square)](https://discord.gg/GWpVpekp) On 🤗Huggingface:[MultiTransformer](https://huggingface.co./MultiTransformer) Math 🔍 [introspector](https://huggingface.co./introspector) On 🌐Github: [Tonic-AI](https://github.com/tonic-ai) & contribute to🌟 [SciTonic](https://github.com/Tonic-AI/scitonic)🤗Big thanks to Yuvi Sharma and all the folks at huggingface for the community grant 🤗
"""

model_path = "bigcode/starcoder2-15b"

hf_token = os.getenv("HF_TOKEN")
if not hf_token:
    raise ValueError("Hugging Face token not found. Please set the HF_TOKEN environment variable.")

tokenizer = AutoTokenizer.from_pretrained(model_path)
quantization_config = BitsAndBytesConfig(load_in_8bit=True)
model = AutoModelForCausalLM.from_pretrained( model_path, quantization_config=quantization_config)

@spaces.GPU
def generate_text(prompt, temperature=0.9, max_length=1200):
    # Encode the inputs
    inputs = tokenizer.encode(prompt, return_tensors="pt")
    attention_mask = torch.ones(inputs.shape, dtype=torch.long)
    inputs = inputs.to("cuda")
    attention_mask = attention_mask.to("cuda")    
    outputs = model.generate(
        inputs, 
        attention_mask=attention_mask,
        max_length=max_length, 
        top_p=0.9, 
        temperature=temperature, 
        do_sample=True, 
        pad_token_id=tokenizer.eos_token_id
    )
    return tokenizer.decode(outputs[0])

def gradio_app():
    with gr.Blocks() as demo:
        gr.Markdown(title)
        prompt = gr.Code(label="Enter your code prompt", value="def print_hello_world():")
        with gr.Row():
            temperature = gr.Slider(minimum=0.1, maximum=1.0, step=0.1, value=0.5, label="Temperature")
            max_length = gr.Slider(minimum=100, maximum=1024, step=10, value=450, label="Generate Length")
        generate_btn = gr.Button("Try✨StarCoder")
        output = gr.Code(label="✨StarCoder:", lines=40)

        generate_btn.click(
            fn=generate_text,
            inputs=[prompt, temperature, max_length],
            outputs=output
        )

    demo.launch()

if __name__ == "__main__":
    gradio_app()