Spaces:
Sleeping
Sleeping
File size: 1,491 Bytes
2b6b068 |
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 |
import gradio as gr
from prompt_generator import generate_prompt
tokenizers = [
"google/gemma-7b",
"meta-llama/Llama-2-7b",
"mistralai/Mistral-7B-v0.1",
"facebook/opt-2.7b",
"microsoft/phi-2",
"THUDM/chatglm3-6b",
"Qwen/Qwen1.5-7B-Chat",
"bigscience/bloom-560m",
"ise-uiuc/Magicoder-S-DS-6.7B",
"google/flan-t5-base",
"TinyLlama/TinyLlama-1.1B-Chat-v1.0",
"google-bert/bert-base-uncased",
]
def generate(model_id, num_tokens):
output_file = f"prompt_{num_tokens}.jsonl"
prompt = generate_prompt(model_id, int(num_tokens), silent=True, output_file=output_file)
return prompt, output_file
demo = gr.Interface(
fn=generate,
title="Prompt Generator",
description="Generate prompts with a given length for testing transformer models. "
"Prompt source: https://archive.org/stream/alicesadventures19033gut/19033.txt",
inputs=[
gr.Dropdown(label="Tokenizer", choices=tokenizers, allow_custom_value=True),
gr.Textbox(label="Number of Tokens"),
],
outputs=[gr.Textbox(label="prompt", show_copy_button=True), gr.File(label="Json file")],
examples=[
["mistralai/Mistral-7B-v0.1", 32],
["mistralai/Mistral-7B-v0.1", 64],
["mistralai/Mistral-7B-v0.1", 128],
["mistralai/Mistral-7B-v0.1", 512],
["mistralai/Mistral-7B-v0.1", 1024],
["mistralai/Mistral-7B-v0.1", 2048],
],
cache_examples=False,
allow_flagging=False,
)
demo.launch()
|